feat: 添加数据库管理平台MCP Server

新增lzwcai-mcp-agile-db项目，提供数据库管理、表操作、数据CRUD、
API密钥管理、技能与工具管理等功能。

包含33个工具：
- 数据源管理：创建、更新、删除数据源
- 数据库与表管理：表结构操作、数据查询等
- API密钥管理：密钥创建、权限管理等
- 技能与工具管理：SQL工具创建、配置更新等
- 数据导入和SQL执行功能

添加了完整的README文档说明安装使用方法，
以及Python 3.12版本支持和基本项目结构。

lzwcai_mcp_agile_db/README.md

@@ -0,0 +1,85 @@
+# lzwcai-mcp-agile-db
+
+数据库管理平台 MCP Server，提供 33 个工具用于数据库管理、表操作、数据 CRUD、API 密钥管理、技能与工具管理等。
+
+## 环境变量
+
+| 变量名 | 必填 | 说明 |
+|--------|------|------|
+| `AGILE_DB_API_KEY` | 是 | 数据库管理平台的 API 密钥 |
+| `AGILE_DB_BASE_URL` | 否 | 数据库管理平台后端地址（默认 `http://localhost:8080`） |
+
+## 安装
+
+```bash
+pip install -e .
+```
+
+## 运行
+
+```bash
+# 设置环境变量
+export AGILE_DB_API_KEY="your-api-key"
+export AGILE_DB_BASE_URL="http://localhost:8080"  # 可选
+
+# 运行 MCP Server
+lzwcai-mcp-agile-db
+```
+
+## 工具列表
+
+### 数据源管理
+- `list_datasources` - 获取数据源列表
+- `get_datasource_detail` - 获取数据源详情
+- `create_datasource` - 创建数据源
+- `update_datasource` - 更新数据源
+- `toggle_datasource_status` - 启用/停用数据源
+- `delete_datasource` - 删除数据源
+
+### 数据库与表管理
+- `list_databases` - 获取数据库列表
+- `list_tables` - 获取表列表
+- `get_table_detail` - 获取表详情
+- `create_table` - 创建表
+- `alter_table` - 修改表结构
+- `generate_table_by_description` - 通过自然语言生成表结构
+
+### 表数据 CRUD
+- `query_table_data` - 查询表数据
+- `insert_table_row` - 插入行数据
+- `update_table_row` - 更新行数据
+- `delete_table_rows` - 删除行数据
+- `export_table_excel` - 导出 Excel
+
+### API 密钥管理
+- `list_api_keys` - 获取密钥列表
+- `create_api_key` - 创建密钥
+- `toggle_api_key_status` - 启用/禁用密钥
+- `delete_api_key` - 删除密钥
+- `get_api_key_permissions` - 查看密钥权限
+- `grant_api_key_permissions` - 授予权限
+
+### 技能与工具管理
+- `get_skill_by_datasource` - 获取技能信息
+- `get_skill_tools` - 获取技能工具列表
+- `create_skill` - 创建技能
+- `create_sql_tool` - 创建 SQL 工具
+- `delete_skill_tool` - 删除技能工具
+- `update_skill_config` - 更新技能配置
+
+### 数据导入
+- `preview_import_data` - 预览导入数据
+- `confirm_import_data` - 确认导入数据
+
+### 表订阅与 SQL 执行
+- `toggle_table_subscription` - 切换表订阅
+- `execute_sql` - 执行 SQL 查询
+
+## 架构
+
+- `tools/_base.py` - 工具注册装饰器和基类
+- `tools/*.py` - 工具实现文件
+- `utils/api_client.py` - 统一 HTTP 客户端
+- `utils/env_config.py` - 环境变量配置
+- `utils/logger_config.py` - 日志配置
+- `server.py` - MCP Server 注册和启动逻辑

lzwcai_mcp_agile_db/lzwcai_mcp_agile_db/.python-version

@@ -0,0 +1 @@
+3.12

lzwcai_mcp_agile_db/lzwcai_mcp_agile_db/__init__.py

@@ -0,0 +1,5 @@
+"""lzwcai-mcp-agile-db MCP Server 包"""
+
+from .server import main
+
+__all__ = ["main"]

lzwcai_mcp_agile_db/lzwcai_mcp_agile_db/logs/lzwcai_mcp_agile_db.log

@@ -0,0 +1,202 @@
+2026-06-11 09:30:49 - root - INFO - [logger_config.py:102] - 日志系统初始化完成 - 日志目录: E:\yh-ai\project\lzwcai-szyg\lzwcai-mcp-server-package\lzwcai_mcp_agile_db\lzwcai_mcp_agile_db\logs
+2026-06-11 09:30:49 - mcp.server.lowlevel.server - DEBUG - [server.py:162] - Initializing server 'lzwcai_mcp_agile_db'
+2026-06-11 09:30:49 - mcp.server.lowlevel.server - DEBUG - [server.py:439] - Registering handler for ListToolsRequest
+2026-06-11 09:30:49 - mcp.server.lowlevel.server - DEBUG - [server.py:519] - Registering handler for CallToolRequest
+2026-06-11 09:30:49 - lzwcai_mcp_agile_db.server - INFO - [server.py:124] - ==================================================
+2026-06-11 09:30:49 - lzwcai_mcp_agile_db.server - INFO - [server.py:125] - lzwcai-mcp-agile-db MCP Server 启动
+2026-06-11 09:30:49 - lzwcai_mcp_agile_db.server - INFO - [server.py:130] - 已注册工具数量: 33
+2026-06-11 09:30:49 - lzwcai_mcp_agile_db.server - INFO - [server.py:131] - ==================================================
+2026-06-11 09:30:49 - lzwcai_mcp_agile_db.server - INFO - [server.py:133] - 开始运行 MCP Server (stdio 模式)
+2026-06-11 09:30:49 - asyncio - DEBUG - [proactor_events.py:634] - Using proactor: IocpProactor
+2026-06-11 09:30:49 - mcp.server.lowlevel.server - DEBUG - [server.py:675] - Received message: root=InitializedNotification(method='notifications/initialized', params=None, jsonrpc='2.0')
+2026-06-11 09:30:50 - mcp.server.lowlevel.server - DEBUG - [server.py:675] - Received message: <mcp.shared.session.RequestResponder object at 0x0000025426747BF0>
+2026-06-11 09:30:50 - mcp.server.lowlevel.server - INFO - [server.py:720] - Processing request of type ListToolsRequest
+2026-06-11 09:30:50 - mcp.server.lowlevel.server - DEBUG - [server.py:723] - Dispatching request of type ListToolsRequest
+2026-06-11 09:30:50 - lzwcai_mcp_agile_db.server - INFO - [server.py:42] - 收到 ListTools 请求
+2026-06-11 09:30:50 - mcp.server.lowlevel.server - DEBUG - [server.py:790] - Response sent
+2026-06-11 09:33:24 - root - INFO - [logger_config.py:102] - 日志系统初始化完成 - 日志目录: E:\yh-ai\project\lzwcai-szyg\lzwcai-mcp-server-package\lzwcai_mcp_agile_db\lzwcai_mcp_agile_db\logs
+2026-06-11 09:33:24 - mcp.server.lowlevel.server - DEBUG - [server.py:162] - Initializing server 'lzwcai_mcp_agile_db'
+2026-06-11 09:33:24 - mcp.server.lowlevel.server - DEBUG - [server.py:439] - Registering handler for ListToolsRequest
+2026-06-11 09:33:24 - mcp.server.lowlevel.server - DEBUG - [server.py:519] - Registering handler for CallToolRequest
+2026-06-11 09:33:24 - lzwcai_mcp_agile_db.server - INFO - [server.py:124] - ==================================================
+2026-06-11 09:33:24 - lzwcai_mcp_agile_db.server - INFO - [server.py:125] - lzwcai-mcp-agile-db MCP Server 启动
+2026-06-11 09:33:24 - lzwcai_mcp_agile_db.server - INFO - [server.py:130] - 已注册工具数量: 33
+2026-06-11 09:33:24 - lzwcai_mcp_agile_db.server - INFO - [server.py:131] - ==================================================
+2026-06-11 09:33:24 - lzwcai_mcp_agile_db.server - INFO - [server.py:133] - 开始运行 MCP Server (stdio 模式)
+2026-06-11 09:33:24 - asyncio - DEBUG - [proactor_events.py:634] - Using proactor: IocpProactor
+2026-06-11 09:33:24 - mcp.server.lowlevel.server - DEBUG - [server.py:675] - Received message: root=InitializedNotification(method='notifications/initialized', params=None, jsonrpc='2.0')
+2026-06-11 09:33:25 - mcp.server.lowlevel.server - DEBUG - [server.py:675] - Received message: <mcp.shared.session.RequestResponder object at 0x0000020155C7D190>
+2026-06-11 09:33:25 - mcp.server.lowlevel.server - INFO - [server.py:720] - Processing request of type ListToolsRequest
+2026-06-11 09:33:25 - mcp.server.lowlevel.server - DEBUG - [server.py:723] - Dispatching request of type ListToolsRequest
+2026-06-11 09:33:25 - lzwcai_mcp_agile_db.server - INFO - [server.py:42] - 收到 ListTools 请求
+2026-06-11 09:33:25 - lzwcai_mcp_agile_db.utils.api_client - INFO - [api_client.py:48] - [客户端初始化] base_url=https://dempdemo.lzwcai.com
+2026-06-11 09:33:25 - lzwcai_mcp_agile_db.server - INFO - [server.py:56] - ListTools 响应: 返回 33 个工具
+2026-06-11 09:33:25 - mcp.server.lowlevel.server - DEBUG - [server.py:790] - Response sent
+2026-06-11 09:33:45 - mcp.server.lowlevel.server - DEBUG - [server.py:675] - Received message: <mcp.shared.session.RequestResponder object at 0x0000020155844410>
+2026-06-11 09:33:45 - mcp.server.lowlevel.server - INFO - [server.py:720] - Processing request of type CallToolRequest
+2026-06-11 09:33:45 - mcp.server.lowlevel.server - DEBUG - [server.py:723] - Dispatching request of type CallToolRequest
+2026-06-11 09:33:45 - lzwcai_mcp_agile_db.server - INFO - [server.py:66] - 收到 CallTool 请求: name=list_datasources
+2026-06-11 09:33:46 - lzwcai_mcp_agile_db.utils.api_client - INFO - [api_client.py:100] - [API请求] GET https://dempdemo.lzwcai.com/api/datasource/connection/list
+2026-06-11 09:33:46 - httpx - DEBUG - [_config.py:82] - load_ssl_context verify=True cert=None trust_env=True http2=False
+2026-06-11 09:33:46 - httpx - DEBUG - [_config.py:148] - load_verify_locations cafile='D:\\anaconda3\\Library\\ssl\\cacert.pem'
+2026-06-11 09:33:46 - httpcore.connection - DEBUG - [_trace.py:47] - connect_tcp.started host='dempdemo.lzwcai.com' port=443 local_address=None timeout=30.0 socket_options=None
+2026-06-11 09:33:46 - httpcore.connection - DEBUG - [_trace.py:47] - connect_tcp.complete return_value=<httpcore._backends.sync.SyncStream object at 0x0000020155E9D8E0>
+2026-06-11 09:33:46 - httpcore.connection - DEBUG - [_trace.py:47] - start_tls.started ssl_context=<ssl.SSLContext object at 0x0000020155E740D0> server_hostname='dempdemo.lzwcai.com' timeout=30.0
+2026-06-11 09:33:46 - httpcore.connection - DEBUG - [_trace.py:47] - start_tls.complete return_value=<httpcore._backends.sync.SyncStream object at 0x0000020155D4CFE0>
+2026-06-11 09:33:46 - httpcore.http11 - DEBUG - [_trace.py:47] - send_request_headers.started request=<Request [b'GET']>
+2026-06-11 09:33:46 - httpcore.http11 - DEBUG - [_trace.py:47] - send_request_headers.complete
+2026-06-11 09:33:46 - httpcore.http11 - DEBUG - [_trace.py:47] - send_request_body.started request=<Request [b'GET']>
+2026-06-11 09:33:46 - httpcore.http11 - DEBUG - [_trace.py:47] - send_request_body.complete
+2026-06-11 09:33:46 - httpcore.http11 - DEBUG - [_trace.py:47] - receive_response_headers.started request=<Request [b'GET']>
+2026-06-11 09:33:46 - httpcore.http11 - DEBUG - [_trace.py:47] - receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'', [(b'Server', b'nginx/1.25.2'), (b'Date', b'Thu, 11 Jun 2026 01:33:40 GMT'), (b'Content-Type', b'application/json;charset=utf-8'), (b'Content-Length', b'51'), (b'Connection', b'keep-alive'), (b'Vary', b'Origin'), (b'Vary', b'Access-Control-Request-Method'), (b'Vary', b'Access-Control-Request-Headers'), (b'X-Content-Type-Options', b'nosniff'), (b'X-XSS-Protection', b'1; mode=block'), (b'X-Frame-Options', b'SAMEORIGIN'), (b'Strict-Transport-Security', b'max-age=31536000; includeSubDomains'), (b'X-Frame-Options', b'DENY'), (b'X-Content-Type-Options', b'nosniff'), (b'X-XSS-Protection', b'1; mode=block')])
+2026-06-11 09:33:46 - httpx - INFO - [_client.py:1038] - HTTP Request: GET https://dempdemo.lzwcai.com/api/datasource/connection/list?pageNum=1&pageSize=20 "HTTP/1.1 200 "
+2026-06-11 09:33:46 - httpcore.http11 - DEBUG - [_trace.py:47] - receive_response_body.started request=<Request [b'GET']>
+2026-06-11 09:33:46 - httpcore.http11 - DEBUG - [_trace.py:47] - receive_response_body.complete
+2026-06-11 09:33:46 - httpcore.http11 - DEBUG - [_trace.py:47] - response_closed.started
+2026-06-11 09:33:46 - httpcore.http11 - DEBUG - [_trace.py:47] - response_closed.complete
+2026-06-11 09:33:46 - lzwcai_mcp_agile_db.utils.api_client - INFO - [api_client.py:74] - [API响应] HTTP 200
+2026-06-11 09:33:46 - lzwcai_mcp_agile_db.utils.api_client - ERROR - [api_client.py:91] - [API错误] 登录过期，请重新登录
+2026-06-11 09:33:46 - lzwcai_mcp_agile_db.server - ERROR - [server.py:96] - 工具执行失败: list_datasources, 错误: 登录过期，请重新登录
+Traceback (most recent call last):
+  File "E:\yh-ai\project\lzwcai-szyg\lzwcai-mcp-server-package\lzwcai_mcp_agile_db\lzwcai_mcp_agile_db\server.py", line 84, in handle_call_tool
+    result = await tool_instance.execute(arguments or {})
+             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "E:\yh-ai\project\lzwcai-szyg\lzwcai-mcp-server-package\lzwcai_mcp_agile_db\lzwcai_mcp_agile_db\tools\datasources.py", line 30, in execute
+    return self.client.get("/api/datasource/connection/list", params=params)
+           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "E:\yh-ai\project\lzwcai-szyg\lzwcai-mcp-server-package\lzwcai_mcp_agile_db\lzwcai_mcp_agile_db\utils\api_client.py", line 102, in get
+    return self._handle_response(response, url)
+           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "E:\yh-ai\project\lzwcai-szyg\lzwcai-mcp-server-package\lzwcai_mcp_agile_db\lzwcai_mcp_agile_db\utils\api_client.py", line 92, in _handle_response
+    raise Exception(error_msg)
+Exception: 登录过期，请重新登录
+2026-06-11 09:33:46 - mcp.server.lowlevel.server - DEBUG - [server.py:790] - Response sent
+2026-06-11 09:39:21 - root - INFO - [logger_config.py:102] - 日志系统初始化完成 - 日志目录: E:\yh-ai\project\lzwcai-szyg\lzwcai-mcp-server-package\lzwcai_mcp_agile_db\lzwcai_mcp_agile_db\logs
+2026-06-11 09:39:21 - mcp.server.lowlevel.server - DEBUG - [server.py:162] - Initializing server 'lzwcai_mcp_agile_db'
+2026-06-11 09:39:21 - mcp.server.lowlevel.server - DEBUG - [server.py:439] - Registering handler for ListToolsRequest
+2026-06-11 09:39:21 - mcp.server.lowlevel.server - DEBUG - [server.py:519] - Registering handler for CallToolRequest
+2026-06-11 09:39:21 - lzwcai_mcp_agile_db.utils.api_client - INFO - [api_client.py:48] - [客户端初始化] base_url=https://dempdemo.lzwcai.com
+2026-06-11 09:39:21 - lzwcai_mcp_agile_db.utils.api_client - INFO - [api_client.py:100] - [API请求] GET https://dempdemo.lzwcai.com/api/datasource/connection/list
+2026-06-11 09:39:21 - httpx - DEBUG - [_config.py:82] - load_ssl_context verify=True cert=None trust_env=True http2=False
+2026-06-11 09:39:21 - httpx - DEBUG - [_config.py:148] - load_verify_locations cafile='C:\\Users\\HiWin10\\AppData\\Local\\Programs\\Python\\Python312\\Lib\\site-packages\\certifi\\cacert.pem'
+2026-06-11 09:39:21 - httpcore.connection - DEBUG - [_trace.py:47] - connect_tcp.started host='dempdemo.lzwcai.com' port=443 local_address=None timeout=30.0 socket_options=None
+2026-06-11 09:39:21 - httpcore.connection - DEBUG - [_trace.py:47] - connect_tcp.complete return_value=<httpcore._backends.sync.SyncStream object at 0x0000027729C00710>
+2026-06-11 09:39:21 - httpcore.connection - DEBUG - [_trace.py:47] - start_tls.started ssl_context=<ssl.SSLContext object at 0x0000027729DFE9D0> server_hostname='dempdemo.lzwcai.com' timeout=30.0
+2026-06-11 09:39:21 - httpcore.connection - DEBUG - [_trace.py:47] - start_tls.complete return_value=<httpcore._backends.sync.SyncStream object at 0x0000027729C23170>
+2026-06-11 09:39:21 - httpcore.http11 - DEBUG - [_trace.py:47] - send_request_headers.started request=<Request [b'GET']>
+2026-06-11 09:39:21 - httpcore.http11 - DEBUG - [_trace.py:47] - send_request_headers.complete
+2026-06-11 09:39:21 - httpcore.http11 - DEBUG - [_trace.py:47] - send_request_body.started request=<Request [b'GET']>
+2026-06-11 09:39:21 - httpcore.http11 - DEBUG - [_trace.py:47] - send_request_body.complete
+2026-06-11 09:39:21 - httpcore.http11 - DEBUG - [_trace.py:47] - receive_response_headers.started request=<Request [b'GET']>
+2026-06-11 09:39:21 - httpcore.http11 - DEBUG - [_trace.py:47] - receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'', [(b'Server', b'nginx/1.25.2'), (b'Date', b'Thu, 11 Jun 2026 01:39:15 GMT'), (b'Content-Type', b'application/json'), (b'Transfer-Encoding', b'chunked'), (b'Connection', b'keep-alive'), (b'Vary', b'Origin'), (b'Vary', b'Access-Control-Request-Method'), (b'Vary', b'Access-Control-Request-Headers'), (b'X-Content-Type-Options', b'nosniff'), (b'X-XSS-Protection', b'1; mode=block'), (b'X-Frame-Options', b'SAMEORIGIN'), (b'Strict-Transport-Security', b'max-age=31536000; includeSubDomains'), (b'X-Frame-Options', b'DENY'), (b'X-Content-Type-Options', b'nosniff'), (b'X-XSS-Protection', b'1; mode=block')])
+2026-06-11 09:39:21 - httpx - INFO - [_client.py:1038] - HTTP Request: GET https://dempdemo.lzwcai.com/api/datasource/connection/list "HTTP/1.1 200 "
+2026-06-11 09:39:21 - httpcore.http11 - DEBUG - [_trace.py:47] - receive_response_body.started request=<Request [b'GET']>
+2026-06-11 09:39:21 - httpcore.http11 - DEBUG - [_trace.py:47] - receive_response_body.complete
+2026-06-11 09:39:21 - httpcore.http11 - DEBUG - [_trace.py:47] - response_closed.started
+2026-06-11 09:39:21 - httpcore.http11 - DEBUG - [_trace.py:47] - response_closed.complete
+2026-06-11 09:39:21 - lzwcai_mcp_agile_db.utils.api_client - INFO - [api_client.py:74] - [API响应] HTTP 200
+2026-06-11 09:39:52 - root - INFO - [logger_config.py:102] - 日志系统初始化完成 - 日志目录: E:\yh-ai\project\lzwcai-szyg\lzwcai-mcp-server-package\lzwcai_mcp_agile_db\lzwcai_mcp_agile_db\logs
+2026-06-11 09:39:52 - mcp.server.lowlevel.server - DEBUG - [server.py:162] - Initializing server 'lzwcai_mcp_agile_db'
+2026-06-11 09:39:52 - mcp.server.lowlevel.server - DEBUG - [server.py:439] - Registering handler for ListToolsRequest
+2026-06-11 09:39:52 - mcp.server.lowlevel.server - DEBUG - [server.py:519] - Registering handler for CallToolRequest
+2026-06-11 09:39:52 - lzwcai_mcp_agile_db.server - INFO - [server.py:124] - ==================================================
+2026-06-11 09:39:52 - lzwcai_mcp_agile_db.server - INFO - [server.py:125] - lzwcai-mcp-agile-db MCP Server 启动
+2026-06-11 09:39:52 - lzwcai_mcp_agile_db.server - INFO - [server.py:130] - 已注册工具数量: 33
+2026-06-11 09:39:52 - lzwcai_mcp_agile_db.server - INFO - [server.py:131] - ==================================================
+2026-06-11 09:39:52 - lzwcai_mcp_agile_db.server - INFO - [server.py:133] - 开始运行 MCP Server (stdio 模式)
+2026-06-11 09:39:52 - asyncio - DEBUG - [proactor_events.py:634] - Using proactor: IocpProactor
+2026-06-11 09:39:52 - mcp.server.lowlevel.server - DEBUG - [server.py:675] - Received message: root=InitializedNotification(method='notifications/initialized', params=None, jsonrpc='2.0')
+2026-06-11 09:39:53 - mcp.server.lowlevel.server - DEBUG - [server.py:675] - Received message: <mcp.shared.session.RequestResponder object at 0x000002B57D06C860>
+2026-06-11 09:39:53 - mcp.server.lowlevel.server - INFO - [server.py:720] - Processing request of type ListToolsRequest
+2026-06-11 09:39:53 - mcp.server.lowlevel.server - DEBUG - [server.py:723] - Dispatching request of type ListToolsRequest
+2026-06-11 09:39:53 - lzwcai_mcp_agile_db.server - INFO - [server.py:42] - 收到 ListTools 请求
+2026-06-11 09:39:53 - lzwcai_mcp_agile_db.utils.api_client - INFO - [api_client.py:48] - [客户端初始化] base_url=https://dempdemo.lzwcai.com
+2026-06-11 09:39:53 - lzwcai_mcp_agile_db.server - INFO - [server.py:56] - ListTools 响应: 返回 33 个工具
+2026-06-11 09:39:53 - mcp.server.lowlevel.server - DEBUG - [server.py:790] - Response sent
+2026-06-11 09:40:08 - mcp.server.lowlevel.server - DEBUG - [server.py:675] - Received message: <mcp.shared.session.RequestResponder object at 0x000002B57D188A40>
+2026-06-11 09:40:08 - mcp.server.lowlevel.server - INFO - [server.py:720] - Processing request of type CallToolRequest
+2026-06-11 09:40:08 - mcp.server.lowlevel.server - DEBUG - [server.py:723] - Dispatching request of type CallToolRequest
+2026-06-11 09:40:08 - lzwcai_mcp_agile_db.server - INFO - [server.py:66] - 收到 CallTool 请求: name=list_datasources
+2026-06-11 09:40:08 - lzwcai_mcp_agile_db.utils.api_client - INFO - [api_client.py:100] - [API请求] GET https://dempdemo.lzwcai.com/api/datasource/connection/list
+2026-06-11 09:40:08 - httpx - DEBUG - [_config.py:82] - load_ssl_context verify=True cert=None trust_env=True http2=False
+2026-06-11 09:40:08 - httpx - DEBUG - [_config.py:148] - load_verify_locations cafile='D:\\anaconda3\\Library\\ssl\\cacert.pem'
+2026-06-11 09:40:08 - httpcore.connection - DEBUG - [_trace.py:47] - connect_tcp.started host='dempdemo.lzwcai.com' port=443 local_address=None timeout=30.0 socket_options=None
+2026-06-11 09:40:08 - httpcore.connection - DEBUG - [_trace.py:47] - connect_tcp.complete return_value=<httpcore._backends.sync.SyncStream object at 0x000002B57D28C560>
+2026-06-11 09:40:08 - httpcore.connection - DEBUG - [_trace.py:47] - start_tls.started ssl_context=<ssl.SSLContext object at 0x000002B57D2642D0> server_hostname='dempdemo.lzwcai.com' timeout=30.0
+2026-06-11 09:40:08 - httpcore.connection - DEBUG - [_trace.py:47] - start_tls.complete return_value=<httpcore._backends.sync.SyncStream object at 0x000002B57CF80410>
+2026-06-11 09:40:08 - httpcore.http11 - DEBUG - [_trace.py:47] - send_request_headers.started request=<Request [b'GET']>
+2026-06-11 09:40:08 - httpcore.http11 - DEBUG - [_trace.py:47] - send_request_headers.complete
+2026-06-11 09:40:08 - httpcore.http11 - DEBUG - [_trace.py:47] - send_request_body.started request=<Request [b'GET']>
+2026-06-11 09:40:08 - httpcore.http11 - DEBUG - [_trace.py:47] - send_request_body.complete
+2026-06-11 09:40:08 - httpcore.http11 - DEBUG - [_trace.py:47] - receive_response_headers.started request=<Request [b'GET']>
+2026-06-11 09:40:08 - httpcore.http11 - DEBUG - [_trace.py:47] - receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'', [(b'Server', b'nginx/1.25.2'), (b'Date', b'Thu, 11 Jun 2026 01:40:02 GMT'), (b'Content-Type', b'application/json'), (b'Transfer-Encoding', b'chunked'), (b'Connection', b'keep-alive'), (b'Vary', b'Origin'), (b'Vary', b'Access-Control-Request-Method'), (b'Vary', b'Access-Control-Request-Headers'), (b'X-Content-Type-Options', b'nosniff'), (b'X-XSS-Protection', b'1; mode=block'), (b'X-Frame-Options', b'SAMEORIGIN'), (b'Strict-Transport-Security', b'max-age=31536000; includeSubDomains'), (b'X-Frame-Options', b'DENY'), (b'X-Content-Type-Options', b'nosniff'), (b'X-XSS-Protection', b'1; mode=block')])
+2026-06-11 09:40:08 - httpx - INFO - [_client.py:1038] - HTTP Request: GET https://dempdemo.lzwcai.com/api/datasource/connection/list?pageNum=1&pageSize=20 "HTTP/1.1 200 "
+2026-06-11 09:40:08 - httpcore.http11 - DEBUG - [_trace.py:47] - receive_response_body.started request=<Request [b'GET']>
+2026-06-11 09:40:08 - httpcore.http11 - DEBUG - [_trace.py:47] - receive_response_body.complete
+2026-06-11 09:40:08 - httpcore.http11 - DEBUG - [_trace.py:47] - response_closed.started
+2026-06-11 09:40:08 - httpcore.http11 - DEBUG - [_trace.py:47] - response_closed.complete
+2026-06-11 09:40:08 - lzwcai_mcp_agile_db.utils.api_client - INFO - [api_client.py:74] - [API响应] HTTP 200
+2026-06-11 09:40:08 - lzwcai_mcp_agile_db.server - INFO - [server.py:86] - 工具执行成功: list_datasources
+2026-06-11 09:40:08 - lzwcai_mcp_agile_db.server - DEBUG - [server.py:87] - 工具返回结果: {
+  "total": 14,
+  "rows": [
+    {
+      "createBy": "",
+      "createTime": "2026-06-10 16:47:43",
+      "updateBy": "",
+      "updateTime": "2026-06-10 16:47:43",
+      "remark": "设备报价管理系统包含设备基础信息、预设方案模板、报价单主表和明细表四个核心数据对象，支持从设备参数管理到整套产线方案配置的完整报价流程，为销售部门提供标准化报价服务，实现快速方案生成和精准成本核算。",
+      "id": "58",
+      "enterpriseId": "1937166012193443842",
+      "deptId": "1171",
+      "userId": "292",
+      "host": "host.docker.internal",
+      "port": 5432,
+      "datasourceName": "HMD产品",
+      "database...
+2026-06-11 09:40:08 - mcp.server.lowlevel.server - DEBUG - [server.py:790] - Response sent
+2026-06-11 09:40:55 - mcp.server.lowlevel.server - DEBUG - [server.py:675] - Received message: <mcp.shared.session.RequestResponder object at 0x000002B57D0617C0>
+2026-06-11 09:40:55 - mcp.server.lowlevel.server - INFO - [server.py:720] - Processing request of type CallToolRequest
+2026-06-11 09:40:55 - mcp.server.lowlevel.server - DEBUG - [server.py:723] - Dispatching request of type CallToolRequest
+2026-06-11 09:40:55 - lzwcai_mcp_agile_db.server - INFO - [server.py:66] - 收到 CallTool 请求: name=list_api_keys
+2026-06-11 09:40:55 - lzwcai_mcp_agile_db.utils.api_client - INFO - [api_client.py:100] - [API请求] GET https://dempdemo.lzwcai.com/api/datasource/api_key/list
+2026-06-11 09:40:55 - httpcore.connection - DEBUG - [_trace.py:47] - close.started
+2026-06-11 09:40:55 - httpcore.connection - DEBUG - [_trace.py:47] - close.complete
+2026-06-11 09:40:55 - httpcore.connection - DEBUG - [_trace.py:47] - connect_tcp.started host='dempdemo.lzwcai.com' port=443 local_address=None timeout=30.0 socket_options=None
+2026-06-11 09:40:55 - httpcore.connection - DEBUG - [_trace.py:47] - connect_tcp.complete return_value=<httpcore._backends.sync.SyncStream object at 0x000002B57D2623C0>
+2026-06-11 09:40:55 - httpcore.connection - DEBUG - [_trace.py:47] - start_tls.started ssl_context=<ssl.SSLContext object at 0x000002B57D2642D0> server_hostname='dempdemo.lzwcai.com' timeout=30.0
+2026-06-11 09:40:55 - httpcore.connection - DEBUG - [_trace.py:47] - start_tls.complete return_value=<httpcore._backends.sync.SyncStream object at 0x000002B57D2626F0>
+2026-06-11 09:40:55 - httpcore.http11 - DEBUG - [_trace.py:47] - send_request_headers.started request=<Request [b'GET']>
+2026-06-11 09:40:55 - httpcore.http11 - DEBUG - [_trace.py:47] - send_request_headers.complete
+2026-06-11 09:40:55 - httpcore.http11 - DEBUG - [_trace.py:47] - send_request_body.started request=<Request [b'GET']>
+2026-06-11 09:40:55 - httpcore.http11 - DEBUG - [_trace.py:47] - send_request_body.complete
+2026-06-11 09:40:55 - httpcore.http11 - DEBUG - [_trace.py:47] - receive_response_headers.started request=<Request [b'GET']>
+2026-06-11 09:40:56 - httpcore.http11 - DEBUG - [_trace.py:47] - receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'', [(b'Server', b'nginx/1.25.2'), (b'Date', b'Thu, 11 Jun 2026 01:40:49 GMT'), (b'Content-Type', b'application/json'), (b'Transfer-Encoding', b'chunked'), (b'Connection', b'keep-alive'), (b'Vary', b'Origin'), (b'Vary', b'Access-Control-Request-Method'), (b'Vary', b'Access-Control-Request-Headers'), (b'X-Content-Type-Options', b'nosniff'), (b'X-XSS-Protection', b'1; mode=block'), (b'X-Frame-Options', b'SAMEORIGIN'), (b'Strict-Transport-Security', b'max-age=31536000; includeSubDomains'), (b'X-Frame-Options', b'DENY'), (b'X-Content-Type-Options', b'nosniff'), (b'X-XSS-Protection', b'1; mode=block')])
+2026-06-11 09:40:56 - httpx - INFO - [_client.py:1038] - HTTP Request: GET https://dempdemo.lzwcai.com/api/datasource/api_key/list?pageNum=1&pageSize=20 "HTTP/1.1 200 "
+2026-06-11 09:40:56 - httpcore.http11 - DEBUG - [_trace.py:47] - receive_response_body.started request=<Request [b'GET']>
+2026-06-11 09:40:56 - httpcore.http11 - DEBUG - [_trace.py:47] - receive_response_body.complete
+2026-06-11 09:40:56 - httpcore.http11 - DEBUG - [_trace.py:47] - response_closed.started
+2026-06-11 09:40:56 - httpcore.http11 - DEBUG - [_trace.py:47] - response_closed.complete
+2026-06-11 09:40:56 - lzwcai_mcp_agile_db.utils.api_client - INFO - [api_client.py:74] - [API响应] HTTP 200
+2026-06-11 09:40:56 - lzwcai_mcp_agile_db.server - INFO - [server.py:86] - 工具执行成功: list_api_keys
+2026-06-11 09:40:56 - lzwcai_mcp_agile_db.server - DEBUG - [server.py:87] - 工具返回结果: {
+  "total": 6,
+  "rows": [
+    {
+      "createBy": "",
+      "createTime": "2026-06-06 15:10:31",
+      "updateBy": "",
+      "updateTime": "2026-06-06 15:10:31",
+      "remark": null,
+      "id": "7",
+      "apiKey": "Lb8LgEJ7eBUU8QMifKUJvo9w6YLAotbKJ-w1DKU8ZrU",
+      "apiKeyName": "AWINBEXT",
+      "enterpriseId": "1937166012193443842",
+      "status": 0,
+      "expireTime": "2027-06-06T15:10:32.000+08:00"
+    },
+    {
+      "createBy": "",
+      "createTime": "2026-05-25 14:47:11",
+      "u...
+2026-06-11 09:40:56 - mcp.server.lowlevel.server - DEBUG - [server.py:790] - Response sent

lzwcai_mcp_agile_db/lzwcai_mcp_agile_db/logs/lzwcai_mcp_agile_db_error.log

@@ -0,0 +1,15 @@
+2026-06-11 09:33:46 - lzwcai_mcp_agile_db.utils.api_client - ERROR - [api_client.py:91] - [API错误] 登录过期，请重新登录
+2026-06-11 09:33:46 - lzwcai_mcp_agile_db.server - ERROR - [server.py:96] - 工具执行失败: list_datasources, 错误: 登录过期，请重新登录
+Traceback (most recent call last):
+  File "E:\yh-ai\project\lzwcai-szyg\lzwcai-mcp-server-package\lzwcai_mcp_agile_db\lzwcai_mcp_agile_db\server.py", line 84, in handle_call_tool
+    result = await tool_instance.execute(arguments or {})
+             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "E:\yh-ai\project\lzwcai-szyg\lzwcai-mcp-server-package\lzwcai_mcp_agile_db\lzwcai_mcp_agile_db\tools\datasources.py", line 30, in execute
+    return self.client.get("/api/datasource/connection/list", params=params)
+           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "E:\yh-ai\project\lzwcai-szyg\lzwcai-mcp-server-package\lzwcai_mcp_agile_db\lzwcai_mcp_agile_db\utils\api_client.py", line 102, in get
+    return self._handle_response(response, url)
+           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "E:\yh-ai\project\lzwcai-szyg\lzwcai-mcp-server-package\lzwcai_mcp_agile_db\lzwcai_mcp_agile_db\utils\api_client.py", line 92, in _handle_response
+    raise Exception(error_msg)
+Exception: 登录过期，请重新登录

lzwcai_mcp_agile_db/lzwcai_mcp_agile_db/main.py

@@ -0,0 +1,6 @@
+def main():
+    print("Hello from lzwcai-mcp-agile-db!")
+
+
+if __name__ == "__main__":
+    main()

lzwcai_mcp_agile_db/lzwcai_mcp_agile_db/pyproject.toml

@@ -0,0 +1,7 @@
+[project]
+name = "lzwcai-mcp-agile-db"
+version = "0.1.0"
+description = "Add your description here"
+readme = "README.md"
+requires-python = ">=3.12"
+dependencies = []

lzwcai_mcp_agile_db/lzwcai_mcp_agile_db/server.py

@@ -0,0 +1,138 @@
+#!/usr/bin/env python3
+"""
+lzwcai-mcp-agile-db MCP Server
+数据库管理平台 MCP 工具服务，提供 33 个工具用于数据库管理、表操作、API 密钥管理等
+"""
+
+import json
+import logging
+import anyio
+
+import mcp.types as types
+from mcp.server import NotificationOptions, Server
+from mcp.server.models import InitializationOptions
+from mcp.server.stdio import stdio_server
+
+from .utils.logger_config import setup_system_logging, get_logger
+from .utils.api_client import AgileDBAPIClient
+from .tools._base import get_registered_tools
+
+# 初始化日志系统
+setup_system_logging(app_name="lzwcai_mcp_agile_db", log_level=logging.DEBUG)
+logger = get_logger(__name__)
+
+# 初始化 MCP Server
+server = Server("lzwcai_mcp_agile_db")
+
+# 全局 API 客户端
+_api_client: AgileDBAPIClient = None
+
+
+def get_api_client() -> AgileDBAPIClient:
+    """获取或创建 API 客户端"""
+    global _api_client
+    if _api_client is None:
+        _api_client = AgileDBAPIClient()
+    return _api_client
+
+
+@server.list_tools()
+async def handle_list_tools() -> list[types.Tool]:
+    """列出所有可用工具"""
+    logger.info("收到 ListTools 请求")
+    
+    tools = []
+    for tool_cls in get_registered_tools():
+        instance = tool_cls(get_api_client())
+        tool_def = instance.to_tool_def()
+        tools.append(
+            types.Tool(
+                name=tool_def["name"],
+                description=tool_def["description"],
+                inputSchema=tool_def["inputSchema"],
+            )
+        )
+    
+    logger.info(f"ListTools 响应: 返回 {len(tools)} 个工具")
+    return tools
+
+
+@server.call_tool()
+async def handle_call_tool(
+    name: str,
+    arguments: dict | None,
+) -> list[types.TextContent | types.ImageContent | types.EmbeddedResource]:
+    """调用工具"""
+    logger.info(f"收到 CallTool 请求: name={name}")
+    
+    # 查找对应的工具类
+    tool_cls = None
+    for cls in get_registered_tools():
+        if cls.name == name:
+            tool_cls = cls
+            break
+    
+    if tool_cls is None:
+        logger.error(f"未找到工具: {name}")
+        raise ValueError(f"未知工具: {name}")
+    
+    # 创建工具实例并执行
+    client = get_api_client()
+    tool_instance = tool_cls(client)
+    
+    try:
+        result = await tool_instance.execute(arguments or {})
+        
+        logger.info(f"工具执行成功: {name}")
+        logger.debug(f"工具返回结果: {json.dumps(result, ensure_ascii=False, indent=2)[:500]}...")
+        
+        return [
+            types.TextContent(
+                type="text",
+                text=json.dumps(result, ensure_ascii=False, indent=2),
+            )
+        ]
+    except Exception as e:
+        logger.error(f"工具执行失败: {name}, 错误: {e}", exc_info=True)
+        return [
+            types.TextContent(
+                type="text",
+                text=json.dumps({"error": str(e), "tool_name": name}, ensure_ascii=False, indent=2),
+            )
+        ]
+
+
+async def run_server():
+    """运行 MCP Server (stdio 模式)"""
+    async with stdio_server() as streams:
+        await server.run(
+            streams[0],
+            streams[1],
+            InitializationOptions(
+                server_name="lzwcai_mcp_agile_db",
+                server_version="0.1.0",
+                capabilities=server.get_capabilities(
+                    notification_options=NotificationOptions(),
+                    experimental_capabilities={},
+                ),
+            ),
+        )
+
+
+def main():
+    """主入口"""
+    logger.info("=" * 50)
+    logger.info("lzwcai-mcp-agile-db MCP Server 启动")
+    
+    # 导入所有工具模块（触发装饰器注册）
+    from . import tools  # noqa: F401
+    
+    logger.info(f"已注册工具数量: {len(get_registered_tools())}")
+    logger.info("=" * 50)
+    
+    logger.info("开始运行 MCP Server (stdio 模式)")
+    anyio.run(run_server)
+
+
+if __name__ == "__main__":
+    main()

lzwcai_mcp_agile_db/lzwcai_mcp_agile_db/tools/__init__.py

@@ -0,0 +1,18 @@
+"""
+工具自动发现模块
+自动导入 tools/ 目录下所有工具模块，触发 @register_tool 装饰器注册
+"""
+
+import importlib
+import pkgutil
+from pathlib import Path
+
+# 获取当前包路径
+_package_path = Path(__file__).parent
+
+# 遍历所有 Python 文件（排除 __init__.py 和 _base.py）
+for _, module_name, _ in pkgutil.iter_modules([str(_package_path)]):
+    if module_name.startswith("_"):
+        continue
+    # 动态导入模块，触发装饰器
+    importlib.import_module(f".{module_name}", __package__)

lzwcai_mcp_agile_db/lzwcai_mcp_agile_db/tools/_base.py

@@ -0,0 +1,116 @@
+"""
+工具注册框架
+提供 ToolDef 基类和 @register_tool 装饰器，用于声明式定义 MCP 工具
+"""
+
+from abc import ABC, abstractmethod
+from typing import Dict, Any, TYPE_CHECKING
+
+if TYPE_CHECKING:
+    from ..utils.api_client import AgileDBAPIClient
+
+
+# 全局工具注册表
+_registered_tools = []
+
+
+def register_tool(name: str):
+    """
+    工具注册装饰器
+    
+    使用方式:
+        @register_tool("list_datasources")
+        class ListDatasourcesTool(ToolDef):
+            name = "list_datasources"
+            description = "获取数据源列表"
+            input_schema = {...}
+            
+            async def execute(self, args):
+                return await self.client.get("/api/...", params=args)
+    
+    Args:
+        name: 工具名称（唯一标识）
+    """
+    def decorator(cls):
+        # 确保类有正确的 name 属性
+        if not hasattr(cls, 'name') or cls.name != name:
+            cls.name = name
+        
+        # 注册到全局列表，避免重复注册
+        if cls not in _registered_tools:
+            _registered_tools.append(cls)
+        return cls
+    
+    return decorator
+
+
+class ToolDef(ABC):
+    """
+    工具定义基类
+    
+    所有工具都应继承此类并使用 @register_tool 装饰器注册
+    
+    类属性:
+        name: 工具名称（唯一标识）
+        description: 工具描述
+        input_schema: JSON Schema 格式的工具输入参数定义
+    
+    实例属性:
+        client: AgileDBAPIClient 实例（由 server 注入）
+    """
+    
+    name: str = ""
+    description: str = ""
+    input_schema: Dict[str, Any] = {"type": "object", "properties": {}, "required": []}
+    
+    def __init__(self, client: "AgileDBAPIClient"):
+        """
+        初始化工具实例
+        
+        Args:
+            client: API 客户端实例（由 server 注入）
+        """
+        self.client = client
+    
+    @abstractmethod
+    async def execute(self, args: Dict[str, Any]) -> Dict[str, Any]:
+        """
+        执行工具逻辑
+        
+        Args:
+            args: 工具输入参数（已校验）
+            
+        Returns:
+            Dict[str, Any]: 执行结果，将作为 MCP 工具返回值
+        """
+        pass
+    
+    def to_tool_def(self) -> Dict[str, Any]:
+        """
+        转换为 MCP 工具定义格式
+        
+        Returns:
+            dict: MCP types.Tool 所需的参数
+        """
+        return {
+            "name": self.name,
+            "description": self.description,
+            "inputSchema": self.input_schema,
+        }
+
+
+def get_registered_tools() -> list:
+    """
+    获取所有已注册的工具类列表
+    
+    Returns:
+        list: 所有被 @register_tool 装饰的类
+    """
+    return list(_registered_tools)
+
+
+def clear_registered_tools():
+    """
+    清空所有已注册的工具（主要用于测试）
+    """
+    _registered_tools.clear()

lzwcai_mcp_agile_db/lzwcai_mcp_agile_db/tools/api_keys.py

@@ -0,0 +1,121 @@
+"""
+API 密钥管理工具 (工具 18-23)
+"""
+
+from ._base import register_tool, ToolDef
+
+
+@register_tool("list_api_keys")
+class ListApiKeysTool(ToolDef):
+    name = "list_api_keys"
+    description = "获取 API 密钥列表"
+    input_schema = {
+        "type": "object",
+        "properties": {
+            "apiKeyName": {"type": "string", "description": "密钥名称模糊搜索"},
+            "pageNum": {"type": "integer", "default": 1, "description": "页码"},
+            "pageSize": {"type": "integer", "default": 20, "description": "每页数量"},
+        },
+        "required": [],
+    }
+
+    async def execute(self, args: dict) -> dict:
+        args = dict(args)
+        params = {k: v for k, v in args.items() if v is not None}
+        return self.client.get("/api/datasource/api_key/list", params=params)
+
+
+@register_tool("create_api_key")
+class CreateApiKeyTool(ToolDef):
+    name = "create_api_key"
+    description = "创建新的 API 密钥"
+    input_schema = {
+        "type": "object",
+        "properties": {
+            "apiKeyName": {"type": "string", "description": "密钥名称（最多50字）"},
+        },
+        "required": ["apiKeyName"],
+    }
+
+    async def execute(self, args: dict) -> dict:
+        return self.client.post("/api/datasource/api_key", json_data=args)
+
+
+@register_tool("toggle_api_key_status")
+class ToggleApiKeyStatusTool(ToolDef):
+    name = "toggle_api_key_status"
+    description = "启用/禁用 API 密钥"
+    input_schema = {
+        "type": "object",
+        "properties": {
+            "id": {"type": "string", "description": "密钥 ID"},
+            "status": {"type": "integer", "enum": [0, 1], "description": "0=启用, 1=禁用"},
+        },
+        "required": ["id", "status"],
+    }
+
+    async def execute(self, args: dict) -> dict:
+        return self.client.put("/api/datasource/api_key", json_data=args)
+
+
+@register_tool("delete_api_key")
+class DeleteApiKeyTool(ToolDef):
+    name = "delete_api_key"
+    description = "删除 API 密钥"
+    input_schema = {
+        "type": "object",
+        "properties": {
+            "id": {"type": "string", "description": "密钥 ID"},
+        },
+        "required": ["id"],
+    }
+
+    async def execute(self, args: dict) -> dict:
+        return self.client.delete(f"/api/datasource/api_key/{args['id']}")
+
+
+@register_tool("get_api_key_permissions")
+class GetApiKeyPermissionsTool(ToolDef):
+    name = "get_api_key_permissions"
+    description = "查看指定密钥的权限配置"
+    input_schema = {
+        "type": "object",
+        "properties": {
+            "apiKeyId": {"type": "string", "description": "密钥 ID"},
+        },
+        "required": ["apiKeyId"],
+    }
+
+    async def execute(self, args: dict) -> dict:
+        return self.client.get(f"/api/datasource/api_key/permission/{args['apiKeyId']}")
+
+
+@register_tool("grant_api_key_permissions")
+class GrantApiKeyPermissionsTool(ToolDef):
+    name = "grant_api_key_permissions"
+    description = "批量为 API 密钥授予权限"
+    input_schema = {
+        "type": "object",
+        "properties": {
+            "apiKeyId": {"type": "string", "description": "密钥 ID"},
+            "batchDatas": {
+                "type": "array",
+                "description": "权限批量数据数组",
+                "items": {
+                    "type": "object",
+                    "properties": {
+                        "connectionId": {"type": "string", "description": "数据源 ID"},
+                        "permissionLevel": {"type": "string", "enum": ["connection", "database", "table"], "description": "权限级别"},
+                        "permissionType": {"type": "string", "description": "权限类型（逗号分隔）"},
+                        "databaseName": {"type": "string", "description": "数据库名（level=database/table 时）"},
+                        "tableName": {"type": "string", "description": "表名（level=table 时）"},
+                    },
+                    "required": ["connectionId", "permissionLevel", "permissionType"],
+                },
+            },
+        },
+        "required": ["apiKeyId", "batchDatas"],
+    }
+
+    async def execute(self, args: dict) -> dict:
+        return self.client.post("/api/datasource/api_key/permission/grant_batch", json_data=args)

lzwcai_mcp_agile_db/lzwcai_mcp_agile_db/tools/data_import.py

@@ -0,0 +1,72 @@
+"""
+数据导入工具 (工具 30-31)
+"""
+
+import base64
+import io
+
+from ._base import register_tool, ToolDef
+
+
+@register_tool("preview_import_data")
+class PreviewImportDataTool(ToolDef):
+    name = "preview_import_data"
+    description = "上传 Excel 文件，AI 智能识别并预览表结构/数据"
+    input_schema = {
+        "type": "object",
+        "properties": {
+            "connectionId": {"type": "string", "description": "数据源 ID"},
+            "target": {"type": "string", "enum": ["prod", "test"], "default": "test", "description": "环境，默认 test"},
+            "file_base64": {"type": "string", "description": "Excel 文件 base64 编码（.xlsx/.xls, <500KB）"},
+            "file_name": {"type": "string", "description": "文件名（如 data.xlsx）"},
+        },
+        "required": ["connectionId", "file_base64"],
+    }
+
+    async def execute(self, args: dict) -> dict:
+        args = dict(args)
+        connection_id = args.pop("connectionId")
+        target = args.pop("target", "test")
+        file_base64 = args.pop("file_base64")
+        file_name = args.pop("file_name", "import.xlsx")
+        
+        # 解码 base64 文件
+        file_content = base64.b64decode(file_base64)
+        
+        # 构建文件上传
+        files = {
+            "file": (file_name, io.BytesIO(file_content), "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"),
+        }
+        
+        return self.client.upload(
+            f"/api/datasource/connection/{connection_id}/import_document/preview",
+            files=files,
+            params={"target": target},
+        )
+
+
+@register_tool("confirm_import_data")
+class ConfirmImportDataTool(ToolDef):
+    name = "confirm_import_data"
+    description = "确认导入 AI 识别后的数据"
+    input_schema = {
+        "type": "object",
+        "properties": {
+            "connectionId": {"type": "string", "description": "数据源 ID"},
+            "target": {"type": "string", "enum": ["prod", "test"], "description": "环境"},
+            "data": {"type": "object", "description": "导入数据（含 tableStructure + allData）"},
+        },
+        "required": ["connectionId", "data"],
+    }
+
+    async def execute(self, args: dict) -> dict:
+        args = dict(args)
+        connection_id = args.pop("connectionId")
+        target = args.pop("target", "test")
+        data = args.pop("data")
+        
+        return self.client.post(
+            f"/api/datasource/connection/{connection_id}/import_document/confirm",
+            json_data=data,
+            params={"target": target},
+        )

lzwcai_mcp_agile_db/lzwcai_mcp_agile_db/tools/database_tables.py

@@ -0,0 +1,151 @@
+"""
+数据库与表管理工具 (工具 7-12)
+"""
+
+from ._base import register_tool, ToolDef
+
+
+@register_tool("list_databases")
+class ListDatabasesTool(ToolDef):
+    name = "list_databases"
+    description = "获取指定数据源下的数据库列表"
+    input_schema = {
+        "type": "object",
+        "properties": {
+            "datasourceId": {"type": "string", "description": "数据源 ID"},
+            "sourceType": {"type": "string", "enum": ["builtin", "external"], "description": "数据源类型"},
+            "pageNum": {"type": "integer", "default": 1, "description": "页码"},
+            "pageSize": {"type": "integer", "default": 20, "description": "每页数量"},
+        },
+        "required": ["datasourceId"],
+    }
+
+    async def execute(self, args: dict) -> dict:
+        params = {k: v for k, v in args.items() if v is not None}
+        return self.client.get("/api/datasource/config/list", params=params)
+
+
+@register_tool("list_tables")
+class ListTablesTool(ToolDef):
+    name = "list_tables"
+    description = "获取指定数据源下的表列表"
+    input_schema = {
+        "type": "object",
+        "properties": {
+            "datasourceId": {"type": "string", "description": "数据源 ID"},
+            "sourceType": {"type": "string", "enum": ["builtin", "external"], "description": "数据源类型"},
+            "pageNum": {"type": "integer", "default": 1, "description": "页码"},
+            "pageSize": {"type": "integer", "default": 20, "description": "每页数量"},
+        },
+        "required": ["datasourceId"],
+    }
+
+    async def execute(self, args: dict) -> dict:
+        params = {k: v for k, v in args.items() if v is not None}
+        return self.client.get("/api/datasource/table/list", params=params)
+
+
+@register_tool("get_table_detail")
+class GetTableDetailTool(ToolDef):
+    name = "get_table_detail"
+    description = "获取表的完整结构信息（字段列表、主键、类型等）"
+    input_schema = {
+        "type": "object",
+        "properties": {
+            "tableId": {"type": "string", "description": "表 ID"},
+        },
+        "required": ["tableId"],
+    }
+
+    async def execute(self, args: dict) -> dict:
+        table_id = args["tableId"]
+        return self.client.get(f"/api/datasource/table/{table_id}/detail")
+
+
+@register_tool("create_table")
+class CreateTableTool(ToolDef):
+    name = "create_table"
+    description = "在指定数据库创建新表"
+    input_schema = {
+        "type": "object",
+        "properties": {
+            "connectionId": {"type": "string", "description": "数据源连接 ID"},
+            "databaseName": {"type": "string", "description": "目标数据库名"},
+            "tableName": {"type": "string", "description": "表名（小写字母+数字+下划线）"},
+            "tableComment": {"type": "string", "description": "表注释"},
+            "columns": {
+                "type": "array",
+                "description": "字段定义数组",
+                "items": {
+                    "type": "object",
+                    "properties": {
+                        "columnName": {"type": "string", "description": "字段名"},
+                        "columnType": {"type": "string", "description": "字段类型（VARCHAR/INTEGER/SERIAL等）"},
+                        "columnLength": {"type": "integer", "description": "字段长度"},
+                        "isPrimaryKey": {"type": "boolean", "description": "是否主键"},
+                        "isNullable": {"type": "boolean", "description": "是否可空"},
+                        "isAutoIncrement": {"type": "boolean", "description": "是否自增"},
+                        "columnComment": {"type": "string", "description": "字段注释"},
+                        "defaultValue": {"type": "string", "description": "默认值"},
+                    },
+                    "required": ["columnName", "columnType"],
+                },
+            },
+        },
+        "required": ["connectionId", "databaseName", "tableName", "columns"],
+    }
+
+    async def execute(self, args: dict) -> dict:
+        args = dict(args)
+        connection_id = args.pop("connectionId")
+        return self.client.post(f"/api/datasource/connection/{connection_id}/create_table", json_data=args)
+
+
+@register_tool("alter_table")
+class AlterTableTool(ToolDef):
+    name = "alter_table"
+    description = "修改已有表结构（增/改/删字段）"
+    input_schema = {
+        "type": "object",
+        "properties": {
+            "connectionId": {"type": "string", "description": "数据源连接 ID"},
+            "databaseName": {"type": "string", "description": "数据库名"},
+            "tableName": {"type": "string", "description": "表名"},
+            "operations": {
+                "type": "array",
+                "description": "表结构变更操作数组",
+                "items": {
+                    "type": "object",
+                    "properties": {
+                        "operation": {"type": "string", "enum": ["ADD_COLUMN", "DROP_COLUMN", "RENAME_COLUMN", "ALTER_COLUMN_TYPE", "SET_NOT_NULL", "DROP_NOT_NULL", "SET_DEFAULT", "DROP_DEFAULT"], "description": "变更类型"},
+                        "column": {"type": "object", "description": "列定义（根据 operation 不同包含不同字段）"},
+                    },
+                    "required": ["operation", "column"],
+                },
+            },
+            "tableComment": {"type": "string", "description": "表注释"},
+        },
+        "required": ["connectionId", "databaseName", "tableName", "operations"],
+    }
+
+    async def execute(self, args: dict) -> dict:
+        args = dict(args)
+        connection_id = args.pop("connectionId")
+        return self.client.put(f"/api/datasource/connection/{connection_id}/alter_table", json_data=args)
+
+
+@register_tool("generate_table_by_description")
+class GenerateTableByDescriptionTool(ToolDef):
+    name = "generate_table_by_description"
+    description = "通过自然语言描述让 AI 生成表结构（异步任务）"
+    input_schema = {
+        "type": "object",
+        "properties": {
+            "requirement": {"type": "string", "description": "业务需求描述"},
+            "databaseId": {"type": "integer", "description": "关联的数据库 ID（可选）"},
+        },
+        "required": ["requirement"],
+    }
+
+    async def execute(self, args: dict) -> dict:
+        return self.client.post("/api/datasource/connection/generate_table", json_data=args)

lzwcai_mcp_agile_db/lzwcai_mcp_agile_db/tools/datasources.py

@@ -0,0 +1,173 @@
+"""
+数据源管理工具 (工具 1-6)
+"""
+
+import logging
+
+from ._base import register_tool, ToolDef
+
+logger = logging.getLogger(__name__)
+
+
+@register_tool("list_datasources")
+class ListDatasourcesTool(ToolDef):
+    name = "list_datasources"
+    description = "获取数据源列表，支持搜索和状态筛选"
+    input_schema = {
+        "type": "object",
+        "properties": {
+            "datasourceName": {"type": "string", "description": "数据源名称模糊搜索"},
+            "status": {"type": "integer", "description": "0=运行中, 1=已停止, 不传=全部"},
+            "sourceType": {"type": "string", "enum": ["builtin", "external"], "description": "数据源类型"},
+            "pageNum": {"type": "integer", "default": 1, "description": "页码"},
+            "pageSize": {"type": "integer", "default": 20, "description": "每页数量"},
+        },
+        "required": [],
+    }
+
+    async def execute(self, args: dict) -> dict:
+        params = {k: v for k, v in args.items() if v is not None}
+        return self.client.get("/api/datasource/connection/list", params=params)
+
+
+@register_tool("get_datasource_detail")
+class GetDatasourceDetailTool(ToolDef):
+    name = "get_datasource_detail"
+    description = "获取单个数据源的完整详情（含配置和实时结构）"
+    input_schema = {
+        "type": "object",
+        "properties": {
+            "datasourceId": {"type": "string", "description": "数据源 ID"},
+        },
+        "required": ["datasourceId"],
+    }
+
+    async def execute(self, args: dict) -> dict:
+        ds_id = args["datasourceId"]
+        result = {}
+        # 获取基本信息
+        try:
+            result["detail"] = self.client.get(f"/api/datasource/connection/{ds_id}")
+        except Exception as e:
+            result["detail"] = {"error": str(e)}
+        # 获取配置
+        try:
+            result["config"] = self.client.get(f"/api/datasource/config/{ds_id}")
+        except Exception as e:
+            result["config"] = {"error": str(e)}
+        # 获取实时结构
+        try:
+            result["structure"] = self.client.get(f"/api/datasource/connection/realtime/structure/{ds_id}")
+        except Exception as e:
+            result["structure"] = {"error": str(e)}
+        return result
+
+
+@register_tool("create_datasource")
+class CreateDatasourceTool(ToolDef):
+    name = "create_datasource"
+    description = "创建外部数据源连接（可选先测试连接）"
+    input_schema = {
+        "type": "object",
+        "properties": {
+            "datasourceName": {"type": "string", "description": "数据源名称（3-20字）"},
+            "datasourceType": {"type": "string", "enum": ["mysql", "postgresql", "oracle", "sqlserver", "dameng"], "description": "数据库类型"},
+            "host": {"type": "string", "description": "数据库地址"},
+            "port": {"type": "integer", "description": "端口号"},
+            "databaseName": {"type": "string", "description": "要连接的数据库名"},
+            "username": {"type": "string", "description": "数据库用户名"},
+            "password": {"type": "string", "description": "密码"},
+            "remark": {"type": "string", "description": "数据源描述"},
+            "connectionType": {"type": "string", "enum": ["user_password", "ssl"], "description": "连接类型，默认 user_password"},
+            "test_first": {"type": "boolean", "default": True, "description": "是否先测试连接，默认 true"},
+        },
+        "required": ["datasourceName", "datasourceType", "host", "port", "databaseName", "username"],
+    }
+
+    async def execute(self, args: dict) -> dict:
+        args = dict(args)
+        test_first = args.pop("test_first", True)
+        
+        # 如果需要先测试连接
+        if test_first:
+            test_data = {
+                "datasourceName": args.get("datasourceName"),
+                "datasourceType": args.get("datasourceType"),
+                "host": args.get("host"),
+                "port": args.get("port"),
+                "databaseName": args.get("databaseName"),
+                "username": args.get("username"),
+                "password": args.get("password"),
+                "connectionType": args.get("connectionType", "user_password"),
+            }
+            test_result = self.client.post("/api/datasource/connection/test", json_data=test_data)
+            if test_result.get("code") != 200:
+                return {"success": False, "error": f"连接测试失败: {test_result.get('msg', '未知错误')}"}
+        
+        # 创建数据源
+        return self.client.post("/api/datasource/connection", json_data=args)
+
+
+@register_tool("update_datasource")
+class UpdateDatasourceTool(ToolDef):
+    name = "update_datasource"
+    description = "更新数据源连接信息"
+    input_schema = {
+        "type": "object",
+        "properties": {
+            "id": {"type": "string", "description": "数据源 ID"},
+            "datasourceName": {"type": "string", "description": "更新名称"},
+            "host": {"type": "string", "description": "更新地址"},
+            "port": {"type": "integer", "description": "更新端口"},
+            "databaseName": {"type": "string", "description": "更新数据库名"},
+            "username": {"type": "string", "description": "更新用户名"},
+            "password": {"type": "string", "description": "新密码（不传则不变）"},
+            "remark": {"type": "string", "description": "更新描述"},
+        },
+        "required": ["id"],
+    }
+
+    async def execute(self, args: dict) -> dict:
+        return self.client.put("/api/datasource/connection", json_data=args)
+
+
+@register_tool("toggle_datasource_status")
+class ToggleDatasourceStatusTool(ToolDef):
+    name = "toggle_datasource_status"
+    description = "启用/停用数据源"
+    input_schema = {
+        "type": "object",
+        "properties": {
+            "id": {"type": "string", "description": "数据源 ID"},
+            "status": {"type": "integer", "enum": [0, 1], "description": "0=启用, 1=停用"},
+        },
+        "required": ["id", "status"],
+    }
+
+    async def execute(self, args: dict) -> dict:
+        return self.client.put("/api/datasource/connection/changeStatus", json_data=args)
+
+
+@register_tool("delete_datasource")
+class DeleteDatasourceTool(ToolDef):
+    name = "delete_datasource"
+    description = "删除数据源（运行中会自动先停用）"
+    input_schema = {
+        "type": "object",
+        "properties": {
+            "id": {"type": "string", "description": "数据源 ID"},
+        },
+        "required": ["id"],
+    }
+
+    async def execute(self, args: dict) -> dict:
+        ds_id = args["id"]
+        # 先尝试停用（仅忽略已停用等预期错误）
+        try:
+            self.client.put("/api/datasource/connection/changeStatus", json_data={"id": ds_id, "status": 1})
+        except Exception as e:
+            # 记录日志但继续删除
+            logger.debug(f"停用数据源失败（可能已停用）: {e}")
+        
+        # 删除数据源
+        return self.client.delete(f"/api/datasource/connection/{ds_id}")

lzwcai_mcp_agile_db/lzwcai_mcp_agile_db/tools/skills.py

@@ -0,0 +1,137 @@
+"""
+技能与工具管理工具 (工具 24-29)
+"""
+
+import json
+
+from ._base import register_tool, ToolDef
+
+
+@register_tool("get_skill_by_datasource")
+class GetSkillByDatasourceTool(ToolDef):
+    name = "get_skill_by_datasource"
+    description = "根据数据源获取技能信息"
+    input_schema = {
+        "type": "object",
+        "properties": {
+            "datasourceId": {"type": "string", "description": "数据源 ID"},
+        },
+        "required": ["datasourceId"],
+    }
+
+    async def execute(self, args: dict) -> dict:
+        return self.client.get(f"/api/datasource/skill/getByDatasource/{args['datasourceId']}")
+
+
+@register_tool("get_skill_tools")
+class GetSkillToolsTool(ToolDef):
+    name = "get_skill_tools"
+    description = "获取技能下的工具列表"
+    input_schema = {
+        "type": "object",
+        "properties": {
+            "skillId": {"type": "string", "description": "技能 ID"},
+        },
+        "required": ["skillId"],
+    }
+
+    async def execute(self, args: dict) -> dict:
+        return self.client.get(f"/api/datasource/skill/getBySkillId/{args['skillId']}")
+
+
+@register_tool("create_skill")
+class CreateSkillTool(ToolDef):
+    name = "create_skill"
+    description = "为数据源创建技能"
+    input_schema = {
+        "type": "object",
+        "properties": {
+            "datasourceId": {"type": "string", "description": "数据源 ID"},
+            "name": {"type": "string", "description": "技能名称（不传则自动生成）"},
+            "description": {"type": "string", "description": "技能描述"},
+        },
+        "required": ["datasourceId"],
+    }
+
+    async def execute(self, args: dict) -> dict:
+        return self.client.post("/api/datasource/skill/createOrGet", json_data=args)
+
+
+@register_tool("create_sql_tool")
+class CreateSqlToolTool(ToolDef):
+    name = "create_sql_tool"
+    description = "将 SQL 查询创建为可复用工具（支持批量）"
+    input_schema = {
+        "type": "object",
+        "properties": {
+            "skillId": {"type": "string", "description": "技能 ID"},
+            "tableIds": {
+                "type": "array",
+                "description": "关联的表 ID 数组",
+                "items": {"type": "string"},
+            },
+            "suggestions": {
+                "type": "array",
+                "description": "SQL 工具建议数组",
+                "items": {
+                    "type": "object",
+                    "properties": {
+                        "name": {"type": "string", "description": "工具名称"},
+                        "businessDescription": {"type": "string", "description": "业务描述"},
+                        "sqlTemplate": {"type": "string", "description": "SQL 模板（支持 #{param} 参数占位）"},
+                        "sqlParams": {"type": "string", "description": "参数 JSON Schema（JSON 字符串或对象）"},
+                        "resultType": {"type": "string", "enum": ["single", "list"], "default": "list", "description": "结果类型，默认 list"},
+                        "businessScenario": {"type": "string", "description": "业务场景描述"},
+                    },
+                    "required": ["name", "businessDescription", "sqlTemplate"],
+                },
+            },
+        },
+        "required": ["skillId", "suggestions"],
+    }
+
+    async def execute(self, args: dict) -> dict:
+        args = dict(args)
+        # 处理 suggestions 中的 sqlParams
+        if "suggestions" in args and isinstance(args["suggestions"], list):
+            for suggestion in args["suggestions"]:
+                if "sqlParams" in suggestion and isinstance(suggestion["sqlParams"], dict):
+                    suggestion["sqlParams"] = json.dumps(suggestion["sqlParams"])
+        return self.client.post("/api/datasource/skill/confirmTools", json_data=args)
+
+
+@register_tool("delete_skill_tool")
+class DeleteSkillToolTool(ToolDef):
+    name = "delete_skill_tool"
+    description = "删除技能下的工具"
+    input_schema = {
+        "type": "object",
+        "properties": {
+            "skillToolId": {"type": "string", "description": "工具 ID"},
+        },
+        "required": ["skillToolId"],
+    }
+
+    async def execute(self, args: dict) -> dict:
+        return self.client.delete(f"/api/datasource/skill/tskilltool/{args['skillToolId']}")
+
+
+@register_tool("update_skill_config")
+class UpdateSkillConfigTool(ToolDef):
+    name = "update_skill_config"
+    description = "更新技能配置（如 MCP Server 配置模板）"
+    input_schema = {
+        "type": "object",
+        "properties": {
+            "datasourceId": {"type": "string", "description": "数据源 ID"},
+            "configTemplate": {"type": "string", "description": "配置模板 JSON 字符串"},
+        },
+        "required": ["datasourceId", "configTemplate"],
+    }
+
+    async def execute(self, args: dict) -> dict:
+        args = dict(args)
+        # 如果 configTemplate 是 dict，转为 JSON 字符串
+        if "configTemplate" in args and isinstance(args["configTemplate"], dict):
+            args["configTemplate"] = json.dumps(args["configTemplate"])
+        return self.client.post("/api/datasource/skill/updateOrGet", json_data=args)

lzwcai_mcp_agile_db/lzwcai_mcp_agile_db/tools/sql_execution.py

@@ -0,0 +1,25 @@
+"""
+SQL 执行工具 (工具 33)
+"""
+
+from ._base import register_tool, ToolDef
+
+
+@register_tool("execute_sql")
+class ExecuteSqlTool(ToolDef):
+    name = "execute_sql"
+    description = "执行原生 SQL 查询"
+    input_schema = {
+        "type": "object",
+        "properties": {
+            "datasourceId": {"type": "string", "description": "数据源 ID"},
+            "executableSql": {"type": "string", "description": "SQL 语句"},
+            "sqlTemplate": {"type": "string", "description": "SQL 模板（可选）"},
+            "businessName": {"type": "string", "description": "业务名称（可选）"},
+            "parameters": {"type": "object", "description": "参数定义（可选）"},
+        },
+        "required": ["datasourceId", "executableSql"],
+    }
+
+    async def execute(self, args: dict) -> dict:
+        return self.client.post("/api/datasource/sqlExecutionLog/testSqlWithSchema", json_data=args)

lzwcai_mcp_agile_db/lzwcai_mcp_agile_db/tools/subscriptions.py

@@ -0,0 +1,23 @@
+"""
+表订阅工具 (工具 32)
+"""
+
+from ._base import register_tool, ToolDef
+
+
+@register_tool("toggle_table_subscription")
+class ToggleTableSubscriptionTool(ToolDef):
+    name = "toggle_table_subscription"
+    description = "切换表的订阅状态"
+    input_schema = {
+        "type": "object",
+        "properties": {
+            "configId": {"type": "string", "description": "数据库配置 ID"},
+            "tableName": {"type": "string", "description": "表名"},
+            "isSubscribe": {"type": "boolean", "description": "true=订阅, false=取消订阅"},
+        },
+        "required": ["configId", "tableName", "isSubscribe"],
+    }
+
+    async def execute(self, args: dict) -> dict:
+        return self.client.post("/api/datasource/subscription/toggle", json_data=args)

lzwcai_mcp_agile_db/lzwcai_mcp_agile_db/tools/table_data.py

@@ -0,0 +1,137 @@
+"""
+表数据 CRUD 工具 (工具 13-17)
+"""
+
+import base64
+
+from ._base import register_tool, ToolDef
+
+
+@register_tool("query_table_data")
+class QueryTableDataTool(ToolDef):
+    name = "query_table_data"
+    description = "查询内置表数据（分页）"
+    input_schema = {
+        "type": "object",
+        "properties": {
+            "tableId": {"type": "string", "description": "表 ID"},
+            "target": {"type": "string", "enum": ["prod", "test"], "default": "prod", "description": "环境，默认 prod"},
+            "pageNum": {"type": "integer", "default": 1, "description": "页码"},
+            "pageSize": {"type": "integer", "default": 10, "description": "每页数量"},
+        },
+        "required": ["tableId"],
+    }
+
+    async def execute(self, args: dict) -> dict:
+        args = dict(args)
+        table_id = args.pop("tableId")
+        params = {k: v for k, v in args.items() if v is not None}
+        return self.client.get(f"/api/datasource/connection/builtin/table/{table_id}", params=params)
+
+
+@register_tool("insert_table_row")
+class InsertTableRowTool(ToolDef):
+    name = "insert_table_row"
+    description = "向内置表插入一行数据"
+    input_schema = {
+        "type": "object",
+        "properties": {
+            "tableId": {"type": "string", "description": "表 ID"},
+            "target": {"type": "string", "enum": ["prod", "test"], "default": "prod", "description": "环境，默认 prod"},
+            "data": {"type": "object", "description": "行数据（键值对，键为字段名）"},
+        },
+        "required": ["tableId", "data"],
+    }
+
+    async def execute(self, args: dict) -> dict:
+        args = dict(args)
+        table_id = args.pop("tableId")
+        target = args.pop("target", "prod")
+        data = args.pop("data", {})
+        params = {"target": target} if target else {}
+        return self.client.post(f"/api/datasource/connection/builtin/table/{table_id}/rows", json_data=data, params=params)
+
+
+@register_tool("update_table_row")
+class UpdateTableRowTool(ToolDef):
+    name = "update_table_row"
+    description = "更新内置表的指定行"
+    input_schema = {
+        "type": "object",
+        "properties": {
+            "tableId": {"type": "string", "description": "表 ID"},
+            "target": {"type": "string", "enum": ["prod", "test"], "default": "prod", "description": "环境，默认 prod"},
+            "primaryKey": {"type": "object", "description": "主键值（如 {\"id\": 1}）"},
+            "data": {"type": "object", "description": "要更新的字段值"},
+        },
+        "required": ["tableId", "primaryKey", "data"],
+    }
+
+    async def execute(self, args: dict) -> dict:
+        args = dict(args)
+        table_id = args.pop("tableId")
+        target = args.pop("target", "prod")
+        primary_key = args.pop("primaryKey")
+        data = args.pop("data", {})
+        params = {"target": target} if target else {}
+        body = {"primaryKey": primary_key, "data": data}
+        return self.client.put(f"/api/datasource/connection/builtin/table/{table_id}/rows", json_data=body, params=params)
+
+
+@register_tool("delete_table_rows")
+class DeleteTableRowsTool(ToolDef):
+    name = "delete_table_rows"
+    description = "删除内置表的指定行（根据主键批量删除）"
+    input_schema = {
+        "type": "object",
+        "properties": {
+            "tableId": {"type": "string", "description": "表 ID"},
+            "target": {"type": "string", "enum": ["prod", "test"], "default": "prod", "description": "环境，默认 prod"},
+            "primaryKeys": {
+                "type": "array",
+                "description": "主键数组（如 [{\"id\": 1}, {\"id\": 2}]）",
+                "items": {"type": "object"},
+            },
+        },
+        "required": ["tableId", "primaryKeys"],
+    }
+
+    async def execute(self, args: dict) -> dict:
+        args = dict(args)
+        table_id = args.pop("tableId")
+        target = args.pop("target", "prod")
+        primary_keys = args.pop("primaryKeys")
+        params = {"target": target} if target else {}
+        body = {"primaryKeys": primary_keys}
+        return self.client.delete(f"/api/datasource/connection/builtin/table/{table_id}/rows", json_data=body, params=params)
+
+
+@register_tool("export_table_excel")
+class ExportTableExcelTool(ToolDef):
+    name = "export_table_excel"
+    description = "导出表数据为 Excel 文件（返回 base64 编码）"
+    input_schema = {
+        "type": "object",
+        "properties": {
+            "tableId": {"type": "string", "description": "表 ID"},
+            "target": {"type": "string", "enum": ["prod", "test"], "default": "prod", "description": "环境，默认 prod"},
+        },
+        "required": ["tableId"],
+    }
+
+    async def execute(self, args: dict) -> dict:
+        args = dict(args)
+        table_id = args.pop("tableId")
+        target = args.pop("target", "prod")
+        params = {"target": target} if target else {}
+        result = self.client.get(f"/api/datasource/connection/builtin/table/{table_id}/export/excel", params=params)
+        
+        # 处理二进制响应
+        if result.get("raw"):
+            content = result["data"]
+            return {
+                "success": True,
+                "file_base64": base64.b64encode(content).decode("utf-8"),
+                "message": "Excel 文件已导出，请解码 base64 内容获取文件",
+            }
+        return result

lzwcai_mcp_agile_db/lzwcai_mcp_agile_db/utils/__init__.py

@@ -0,0 +1,13 @@
+from .env_config import get_api_key, get_base_url, get_env_config
+from .logger_config import setup_system_logging, get_logger
+from .api_client import AgileDBAPIClient, get_default_client
+
+__all__ = [
+    'get_api_key',
+    'get_base_url',
+    'get_env_config',
+    'setup_system_logging',
+    'get_logger',
+    'AgileDBAPIClient',
+    'get_default_client',
+]

lzwcai_mcp_agile_db/lzwcai_mcp_agile_db/utils/api_client.py

@@ -0,0 +1,196 @@
+"""
+数据库管理平台 API 调用客户端
+用于调用数据库管理平台的所有 API 接口
+"""
+
+import httpx
+import json
+import os
+from typing import Dict, Any, Optional
+
+from .env_config import get_api_key, get_base_url
+from .logger_config import get_logger
+
+logger = get_logger(__name__)
+
+# 默认超时配置（秒）
+DEFAULT_TIMEOUT = 30.0
+
+
+class AgileDBAPIClient:
+    """数据库管理平台 API 客户端"""
+    
+    def __init__(
+        self, 
+        base_url: Optional[str] = None,
+        api_key: Optional[str] = None,
+        default_timeout: float = DEFAULT_TIMEOUT,
+    ):
+        """
+        初始化 API 客户端
+        
+        Args:
+            base_url: API 基础 URL（默认从环境变量 AGILE_DB_BASE_URL 读取）
+            api_key: API 密钥（默认从环境变量 AGILE_DB_API_KEY 读取）
+            default_timeout: 请求超时时间（秒），默认 30 秒
+        """
+        if base_url is None:
+            base_url = get_base_url()
+        
+        if api_key is None:
+            api_key = get_api_key()
+        
+        self.base_url = base_url.rstrip('/')
+        self.api_key = api_key
+        self.default_timeout = default_timeout
+        self._client: Optional[httpx.Client] = None
+        
+        logger.info(f"[客户端初始化] base_url={self.base_url}")
+    
+    @property
+    def client(self) -> httpx.Client:
+        """懒加载 HTTP 客户端"""
+        if self._client is None:
+            self._client = httpx.Client(timeout=self.default_timeout)
+        return self._client
+        
+    def _get_headers(self, extra_headers: Optional[Dict[str, str]] = None) -> Dict[str, str]:
+        """获取请求头"""
+        headers = {
+            'Authorization': self.api_key if self.api_key.startswith('Bearer ') else f'Bearer {self.api_key}',
+        }
+        if extra_headers:
+            headers.update(extra_headers)
+        return headers
+    
+    def _build_url(self, path: str) -> str:
+        """构建完整 URL"""
+        if path.startswith('http://') or path.startswith('https://'):
+            return path
+        return f"{self.base_url}{path}"
+    
+    def _handle_response(self, response: httpx.Response, url: str) -> Dict[str, Any]:
+        """统一处理 API 响应"""
+        logger.info(f"[API响应] HTTP {response.status_code}")
+        
+        if response.status_code == 204:
+            return {"success": True, "data": None}
+        
+        response.raise_for_status()
+        
+        try:
+            data = response.json()
+        except json.JSONDecodeError:
+            # 非 JSON 响应（如文件下载）
+            return {"success": True, "data": response.content, "raw": True}
+        
+        # 检查平台 API 的 {code, msg} 格式
+        if isinstance(data, dict) and 'code' in data:
+            if data['code'] != 200:
+                error_msg = data.get('msg', '未知错误')
+                logger.error(f"[API错误] {error_msg}")
+                raise Exception(error_msg)
+        
+        return data
+    
+    def get(self, path: str, params: Optional[Dict[str, Any]] = None) -> Dict[str, Any]:
+        """发送 GET 请求"""
+        url = self._build_url(path)
+        try:
+            logger.info(f"[API请求] GET {url}")
+            response = self.client.get(url, headers=self._get_headers(), params=params)
+            return self._handle_response(response, url)
+        except httpx.TimeoutException:
+            raise Exception(f"API 请求超时: {url}")
+        except httpx.HTTPStatusError as e:
+            raise Exception(f"API 请求失败 (HTTP {e.response.status_code}): {url}")
+        except httpx.RequestError as e:
+            raise Exception(f"API 请求异常: {url}, 错误: {str(e)}")
+
+    def post(self, path: str, json_data: Optional[Dict[str, Any]] = None, params: Optional[Dict[str, Any]] = None) -> Dict[str, Any]:
+        """发送 POST 请求"""
+        url = self._build_url(path)
+        try:
+            logger.info(f"[API请求] POST {url}")
+            headers = self._get_headers({'Content-Type': 'application/json'})
+            response = self.client.post(url, headers=headers, json=json_data, params=params)
+            return self._handle_response(response, url)
+        except httpx.TimeoutException:
+            raise Exception(f"API 请求超时: {url}")
+        except httpx.HTTPStatusError as e:
+            raise Exception(f"API 请求失败 (HTTP {e.response.status_code}): {url}")
+        except httpx.RequestError as e:
+            raise Exception(f"API 请求异常: {url}, 错误: {str(e)}")
+
+    def put(self, path: str, json_data: Optional[Dict[str, Any]] = None, params: Optional[Dict[str, Any]] = None) -> Dict[str, Any]:
+        """发送 PUT 请求"""
+        url = self._build_url(path)
+        try:
+            logger.info(f"[API请求] PUT {url}")
+            headers = self._get_headers({'Content-Type': 'application/json'})
+            response = self.client.put(url, headers=headers, json=json_data, params=params)
+            return self._handle_response(response, url)
+        except httpx.TimeoutException:
+            raise Exception(f"API 请求超时: {url}")
+        except httpx.HTTPStatusError as e:
+            raise Exception(f"API 请求失败 (HTTP {e.response.status_code}): {url}")
+        except httpx.RequestError as e:
+            raise Exception(f"API 请求异常: {url}, 错误: {str(e)}")
+
+    def delete(self, path: str, params: Optional[Dict[str, Any]] = None, json_data: Optional[Dict[str, Any]] = None) -> Dict[str, Any]:
+        """发送 DELETE 请求"""
+        url = self._build_url(path)
+        try:
+            logger.info(f"[API请求] DELETE {url}")
+            headers = self._get_headers()
+            if json_data is not None:
+                headers['Content-Type'] = 'application/json'
+            response = self.client.delete(url, headers=headers, params=params, json=json_data)
+            return self._handle_response(response, url)
+        except httpx.TimeoutException:
+            raise Exception(f"API 请求超时: {url}")
+        except httpx.HTTPStatusError as e:
+            raise Exception(f"API 请求失败 (HTTP {e.response.status_code}): {url}")
+        except httpx.RequestError as e:
+            raise Exception(f"API 请求异常: {url}, 错误: {str(e)}")
+
+    def upload(self, path: str, files: Dict[str, Any], params: Optional[Dict[str, Any]] = None) -> Dict[str, Any]:
+        """发送文件上传请求（multipart/form-data）"""
+        url = self._build_url(path)
+        try:
+            logger.info(f"[API请求] UPLOAD {url}")
+            # 文件上传不需要 Content-Type，httpx 会自动设置 multipart/form-data
+            headers = self._get_headers()
+            response = self.client.post(url, headers=headers, files=files, params=params)
+            return self._handle_response(response, url)
+        except httpx.TimeoutException:
+            raise Exception(f"API 请求超时: {url}")
+        except httpx.HTTPStatusError as e:
+            raise Exception(f"API 请求失败 (HTTP {e.response.status_code}): {url}")
+        except httpx.RequestError as e:
+            raise Exception(f"API 请求异常: {url}, 错误: {str(e)}")
+
+    def close(self):
+        """关闭 HTTP 客户端"""
+        if self._client is not None:
+            self._client.close()
+            self._client = None
+    
+    def __enter__(self):
+        return self
+    
+    def __exit__(self, exc_type, exc_val, exc_tb):
+        self.close()
+        return False
+
+
+# 懒加载的默认客户端
+_default_client: Optional[AgileDBAPIClient] = None
+
+
+def get_default_client() -> AgileDBAPIClient:
+    """获取默认客户端（懒加载）"""
+    global _default_client
+    if _default_client is None:
+        _default_client = AgileDBAPIClient()
+    return _default_client

lzwcai_mcp_agile_db/lzwcai_mcp_agile_db/utils/env_config.py

@@ -0,0 +1,60 @@
+"""环境变量配置模块 - 数据库管理平台 MCP Server"""
+
+import os
+from typing import Optional
+
+
+def get_api_key(default: Optional[str] = None) -> str:
+    """
+    获取数据库管理平台 API 密钥
+    
+    Args:
+        default: 默认值（可选）
+        
+    Returns:
+        str: API 密钥
+        
+    Raises:
+        ValueError: 当 AGILE_DB_API_KEY 未设置且无默认值时
+    """
+    value = os.environ.get("AGILE_DB_API_KEY", default or "")
+    if not value:
+        raise ValueError("环境变量 AGILE_DB_API_KEY 未设置")
+    return value
+
+
+def get_base_url(default: str = "http://localhost:8080") -> str:
+    """
+    获取数据库管理平台后端地址
+    
+    Args:
+        default: 默认值（默认 http://localhost:8080）
+        
+    Returns:
+        str: 后端 API 基础 URL
+    """
+    return os.environ.get("AGILE_DB_BASE_URL", default)
+
+
+def get_env_config() -> dict:
+    """
+    获取所有环境配置
+    
+    Returns:
+        dict: 包含所有配置的字典
+    """
+    return {
+        "api_key": get_api_key(""),
+        "base_url": get_base_url(),
+    }
+
+
+def set_env_variable(key: str, value: str) -> None:
+    """
+    设置环境变量（仅在当前进程中有效）
+    
+    Args:
+        key: 环境变量名
+        value: 环境变量值
+    """
+    os.environ[key] = value

lzwcai_mcp_agile_db/lzwcai_mcp_agile_db/utils/logger_config.py

@@ -0,0 +1,121 @@
+# -*- coding: utf-8 -*-
+"""
+统一日志配置模块
+提供系统级别的日志配置和管理
+"""
+
+import os
+import sys
+import logging
+from logging.handlers import RotatingFileHandler
+from pathlib import Path
+
+
+class LoggerConfig:
+    """日志配置管理类"""
+    
+    def __init__(self, logs_dir: str = None):
+        """初始化日志配置
+        
+        Args:
+            logs_dir: 日志目录路径，默认为项目根目录下的logs文件夹
+        """
+        if logs_dir:
+            self.logs_dir = Path(logs_dir)
+        else:
+            project_root = Path(__file__).parent.parent
+            self.logs_dir = project_root / "logs"
+        
+        self.logs_dir.mkdir(exist_ok=True)
+        
+        self.log_format = '%(asctime)s - %(name)s - %(levelname)s - [%(filename)s:%(lineno)d] - %(message)s'
+        self.date_format = '%Y-%m-%d %H:%M:%S'
+        self.log_level = self._get_log_level_from_env()
+        self._initialized = False
+    
+    def _get_log_level_from_env(self) -> int:
+        log_level_str = os.getenv('LOG_LEVEL', 'INFO').upper()
+        level_mapping = {
+            'DEBUG': logging.DEBUG,
+            'INFO': logging.INFO,
+            'WARNING': logging.WARNING,
+            'WARN': logging.WARNING,
+            'ERROR': logging.ERROR,
+            'CRITICAL': logging.CRITICAL,
+            'FATAL': logging.CRITICAL
+        }
+        return level_mapping.get(log_level_str, logging.INFO)
+    
+    def setup_logging(self, 
+                     app_name: str = "lzwcai_mcp_agile_db",
+                     log_level: int = logging.INFO,
+                     max_file_size: int = 10 * 1024 * 1024,
+                     backup_count: int = 5,
+                     console_output: bool = True) -> logging.Logger:
+        if self._initialized:
+            return logging.getLogger()
+        
+        root_logger = logging.getLogger()
+        root_logger.setLevel(log_level)
+        
+        for handler in root_logger.handlers[:]:
+            root_logger.removeHandler(handler)
+        
+        formatter = logging.Formatter(self.log_format, self.date_format)
+
+        # 1. 主日志文件 - 按大小滚动
+        main_log_file = self.logs_dir / f"{app_name}.log"
+        file_handler = RotatingFileHandler(
+            main_log_file,
+            maxBytes=max_file_size,
+            backupCount=backup_count,
+            encoding='utf-8'
+        )
+        file_handler.setLevel(log_level)
+        file_handler.setFormatter(formatter)
+        root_logger.addHandler(file_handler)
+        
+        # 2. 错误日志文件
+        error_log_file = self.logs_dir / f"{app_name}_error.log"
+        error_handler = RotatingFileHandler(
+            error_log_file,
+            maxBytes=max_file_size,
+            backupCount=backup_count,
+            encoding='utf-8'
+        )
+        error_handler.setLevel(logging.ERROR)
+        error_handler.setFormatter(formatter)
+        root_logger.addHandler(error_handler)
+        
+        # 3. 控制台输出 (MCP协议使用stdio时，必须将日志输出到stderr)
+        if console_output:
+            console_handler = logging.StreamHandler(sys.stderr)
+            console_handler.setLevel(log_level)
+            console_formatter = logging.Formatter(
+                '%(asctime)s - %(name)s - %(levelname)s - %(message)s',
+                self.date_format
+            )
+            console_handler.setFormatter(console_formatter)
+            root_logger.addHandler(console_handler)
+        
+        self._initialized = True
+        root_logger.info(f"日志系统初始化完成 - 日志目录: {self.logs_dir}")
+        
+        return root_logger
+    
+    def get_module_logger(self, name: str) -> logging.Logger:
+        """获取模块级别的 logger（继承根配置）"""
+        return logging.getLogger(name)
+
+
+# 全局日志配置实例
+logger_config = LoggerConfig()
+
+
+def setup_system_logging(app_name: str = "lzwcai_mcp_agile_db", 
+                        log_level: int = logging.INFO) -> logging.Logger:
+    return logger_config.setup_logging(app_name, log_level)
+
+
+def get_logger(name: str) -> logging.Logger:
+    return logger_config.get_module_logger(name)

lzwcai_mcp_agile_db/lzwcai_mcp_agile_db/数据库管理平台-MCP工具设计方案.md

@@ -0,0 +1,621 @@
+# 数据库管理平台 - MCP 工具设计方案
+
+> 基于平台现有功能，设计可供外部 AI Agent 通过 MCP 协议调用的工具集。
+> 目标：**用户脱离平台界面，通过 MCP 调用即可使用数据库管理平台的核心功能。**
+
+---
+
+## 一、设计原则
+
+1. **按用户场景分组**：不是简单映射 API，而是围绕用户真实工作流组织工具
+2. **最小化调用链**：复杂操作尽量合并为一个 tool，减少多轮调用
+3. **读写分离**：查询类工具可安全暴露，写操作需明确提示
+4. **环境感知**：所有操作默认携带环境参数(prod/test)，内置数据源特有
+5. **权限前置**：调用方需提供 apiKeyId 或等效凭证，工具内部自动鉴权
+
+---
+
+## 二、工具清单
+
+### 🗄️ 数据源管理
+
+#### 1. `list_datasources`
+- **用途**：获取数据源列表，支持搜索和状态筛选
+- **对应前端**：DataSourceList.vue
+- **对应 API**：`getConnectionList` ✅ 已实现
+  - **端点**：`GET /api/datasource/connection/list`
+
+| 参数 | 类型 | 必填 | 说明 |
+|------|------|------|------|
+| datasourceName | string | 否 | 数据源名称模糊搜索 |
+| status | int | 否 | 0=运行中, 1=已停止, 不传=全部 |
+| sourceType | string | 否 | builtin/external |
+| pageNum | int | 否 | 默认 1 |
+| pageSize | int | 否 | 默认 20 |
+
+**返回**：数据源列表（含名称、类型、状态、库数、表数、创建时间等）
+
+---
+
+#### 2. `get_datasource_detail`
+- **用途**：获取单个数据源的完整详情
+- **对应前端**：DatabaseDetail.vue 头部
+- **对应 API**：
+  - `getConnectionDetail(id)` ✅ 已实现 — `GET /api/datasource/connection/{id}`
+  - `getConnectionConfig(id)` ✅ 已实现 — `GET /api/datasource/config/{id}`
+  - `getConnectionRealtimeStructure(id)` ✅ 已实现 — `GET /api/datasource/connection/realtime/structure/{id}`
+
+| 参数 | 类型 | 必填 | 说明 |
+|------|------|------|------|
+| datasourceId | string | 是 | 数据源 ID |
+
+**返回**：数据源详情 + 数据库配置列表 + 实时结构（数据库列表、表列表、字段信息）
+
+---
+
+#### 3. `create_datasource`
+- **用途**：创建外部数据源连接
+- **对应前端**：CreateDataSource.vue
+- **对应 API**：
+  - `testConnection(data)` ✅ 已实现 — `POST /api/datasource/connection/test`
+  - `postConnectionDetail(data)` ✅ 已实现 — `POST /api/datasource/connection`
+
+| 参数 | 类型 | 必填 | 说明 |
+|------|------|------|------|
+| datasourceName | string | 是 | 数据源名称（3-20字） |
+| datasourceType | string | 是 | mysql/postgresql/oracle/sqlserver/dameng |
+| host | string | 是 | 数据库地址 |
+| port | int | 是 | 端口号 |
+| databaseName | string | 是 | 要连接的数据库名 |
+| username | string | 是 | 数据库用户名 |
+| password | string | 否 | 密码 |
+| remark | string | 否 | 数据源描述 |
+| connectionType | string | 否 | user_password/ssl，默认 user_password |
+| test_first | bool | 否 | 是否先测试连接，默认 true |
+
+**返回**：创建结果，含数据源 ID
+
+---
+
+#### 4. `update_datasource`
+- **用途**：更新数据源连接信息
+- **对应 API**：`putConnectionDetail(data)` ✅ 已实现 — `PUT /api/datasource/connection`
+
+| 参数 | 类型 | 必填 | 说明 |
+|------|------|------|------|
+| id | string | 是 | 数据源 ID |
+| datasourceName | string | 否 | 更新名称 |
+| host | string | 否 | 更新地址 |
+| port | int | 否 | 更新端口 |
+| databaseName | string | 否 | 更新数据库名 |
+| username | string | 否 | 更新用户名 |
+| password | string | 否 | 新密码（不传则不变） |
+| remark | string | 否 | 更新描述 |
+
+**返回**：更新结果
+
+---
+
+#### 5. `toggle_datasource_status`
+- **用途**：启用/停用数据源
+- **对应 API**：`putConnectionChangeStatus(data)` ✅ 已实现 — `PUT /api/datasource/connection/changeStatus`
+
+| 参数 | 类型 | 必填 | 说明 |
+|------|------|------|------|
+| id | string | 是 | 数据源 ID |
+| status | int | 是 | 0=启用, 1=停用 |
+
+**返回**：操作结果
+
+---
+
+#### 6. `delete_datasource`
+- **用途**：删除数据源（运行中会自动先停用）
+- **对应 API**：
+  - `putConnectionChangeStatus(data)` ✅ 已实现 — `PUT /api/datasource/connection/changeStatus`
+  - `deleteConnection(id)` ✅ 已实现 — `DELETE /api/datasource/connection/{id}`
+
+| 参数 | 类型 | 必填 | 说明 |
+|------|------|------|------|
+| id | string | 是 | 数据源 ID |
+
+**返回**：删除结果
+
+---
+
+### 📊 数据库与表管理
+
+#### 7. `list_databases`
+- **用途**：获取指定数据源下的数据库列表
+- **对应 API**：`getConnectionConfigList(data)` ✅ 已实现 — `GET /api/datasource/config/list`
+
+| 参数 | 类型 | 必填 | 说明 |
+|------|------|------|------|
+| datasourceId | string | 是 | 数据源 ID |
+
+**返回**：数据库列表（ID、名称、类型、状态、表数）
+
+---
+
+#### 8. `list_tables`
+- **用途**：获取指定数据库下的表列表
+- **对应前端**：DatabaseDetail.vue 左侧表列表
+- **对应 API**：`getTableList(data)` ✅ 已实现 — `GET /api/datasource/table/list`
+
+| 参数 | 类型 | 必填 | 说明 |
+|------|------|------|------|
+| datasourceId | string | 是 | 数据源 ID |
+| databaseName | string | 否 | 数据库名过滤 |
+| keyword | string | 否 | 表名模糊搜索 |
+| pageNum | int | 否 | 默认 1 |
+| pageSize | int | 否 | 默认 20 |
+
+**返回**：表列表（表名、注释、字段数、创建时间等）
+
+---
+
+#### 9. `get_table_detail`
+- **用途**：获取表的完整结构信息
+- **对应前端**：DatabaseDetail.vue 右侧字段列表
+- **对应 API**：`getTableDetail(id)` ✅ 已实现 — `GET /api/datasource/table/{id}/detail`
+
+| 参数 | 类型 | 必填 | 说明 |
+|------|------|------|------|
+| tableId | string | 是 | 表 ID |
+
+**返回**：表名、表注释、字段列表（字段名、类型、长度、主键、可空、默认值、注释、AI训练状态）
+
+---
+
+#### 10. `create_table`
+- **用途**：在指定数据库创建新表
+- **对应前端**：CreateBuiltinDataSource.vue 表结构编辑器
+- **对应 API**：`postCreateTable(connectionId, data)` ✅ 已实现 — `POST /api/datasource/connection/{connectionId}/create_table`
+
+| 参数 | 类型 | 必填 | 说明 |
+|------|------|------|------|
+| datasourceId | string | 是 | 数据源 ID |
+| databaseName | string | 是 | 目标数据库名 |
+| tableName | string | 是 | 表名（小写字母+数字+下划线） |
+| tableComment | string | 否 | 表注释 |
+| columns | array | 是 | 字段定义数组 |
+| columns[].columnName | string | 是 | 字段名 |
+| columns[].columnType | string | 是 | 字段类型（VARCHAR/INTEGER/SERIAL等） |
+| columns[].columnLength | int | 否 | 字段长度 |
+| columns[].isPrimaryKey | bool | 否 | 是否主键 |
+| columns[].isNullable | bool | 否 | 是否可空 |
+| columns[].isAutoIncrement | bool | 否 | 是否自增 |
+| columns[].columnComment | string | 否 | 字段注释 |
+| columns[].defaultValue | string | 否 | 默认值 |
+
+**返回**：创建结果，含表 ID
+
+---
+
+#### 11. `alter_table`
+- **用途**：修改已有表结构（增/改/删字段）
+- **对应 API**：`putAlterTable(connectionId, data)` ✅ 已实现 — `PUT /api/datasource/connection/{connectionId}/alter_table`
+
+| 参数 | 类型 | 必填 | 说明 |
+|------|------|------|------|
+| tableId | string | 是 | 表 ID |
+| columns | array | 是 | 字段变更数组 |
+| columns[].operation | string | 是 | ADD_COLUMN / MODIFY_COLUMN / DROP_COLUMN |
+| columns[].columnName | string | 是 | 字段名 |
+| columns[].columnType | string | 否 | 字段类型（ADD/MODIFY） |
+| columns[].columnLength | int | 否 | 字段长度 |
+| columns[].isPrimaryKey | bool | 否 | 是否主键 |
+| columns[].isNullable | bool | 否 | 是否可空 |
+| columns[].columnComment | string | 否 | 字段注释 |
+| columns[].defaultValue | string | 否 | 默认值 |
+| newTableName | string | 否 | 新表名（重命名） |
+| newTableComment | string | 否 | 新表注释 |
+
+**返回**：修改结果
+
+---
+
+#### 12. `generate_table_by_description`
+- **用途**：通过自然语言描述让 AI 生成表结构
+- **对应前端**：CreateBuiltinDataSource.vue AI 生成表结构
+- **对应 API**：`postGenerateTable(data)` ✅ 已实现 — `POST /api/datasource/connection/generate_table`
+
+| 参数 | 类型 | 必填 | 说明 |
+|------|------|------|------|
+| description | string | 是 | 业务场景描述（至少6个字符） |
+
+**返回**：AI 生成的表结构（表名、表注释、字段列表含类型/主键/注释等）
+
+> **场景示例**：用户说"我需要一个商城系统，管理商品、分类和用户评价"，AI 返回完整的表结构设计。
+
+---
+
+### 📝 表数据操作 (内置数据源 CRUD)
+
+#### 13. `query_table_data`
+- **用途**：查询内置表数据（分页）
+- **对应前端**：CustomizeDbTable.vue 线上/调试数据视图
+- **对应 API**：`getBuiltinTableData(tableId, params)` ✅ 已实现 — `GET /api/datasource/connection/builtin/table/{tableId}`
+
+| 参数 | 类型 | 必填 | 说明 |
+|------|------|------|------|
+| tableId | string | 是 | 表 ID |
+| target | string | 否 | prod/test，默认 prod |
+| pageNum | int | 否 | 默认 1 |
+| pageSize | int | 否 | 默认 10 |
+
+**返回**：表结构信息 + 数据行（二维数组转换后的对象数组） + 总数
+
+---
+
+#### 14. `insert_table_row`
+- **用途**：向内置表插入一行数据
+- **对应 API**：`postBuiltinTableRows(tableId, data, params)` ✅ 已实现 — `POST /api/datasource/connection/builtin/table/{tableId}/rows`
+
+| 参数 | 类型 | 必填 | 说明 |
+|------|------|------|------|
+| tableId | string | 是 | 表 ID |
+| target | string | 否 | prod/test，默认 prod |
+| data | object | 是 | 行数据（键值对，键为字段名） |
+
+**返回**：插入结果
+
+---
+
+#### 15. `update_table_row`
+- **用途**：更新内置表的指定行
+- **对应 API**：`putBuiltinTableRows(tableId, data, params)` ✅ 已实现 — `PUT /api/datasource/connection/builtin/table/{tableId}/rows`
+
+| 参数 | 类型 | 必填 | 说明 |
+|------|------|------|------|
+| tableId | string | 是 | 表 ID |
+| target | string | 否 | prod/test，默认 prod |
+| primaryKey | object | 是 | 主键值（如 {"id": 1}） |
+| data | object | 是 | 要更新的字段值 |
+
+**返回**：更新结果
+
+---
+
+#### 16. `delete_table_rows`
+- **用途**：删除内置表的指定行
+- **对应 API**：`deleteBuiltinTableRows(tableId, data, params)` ✅ 已实现 — `DELETE /api/datasource/connection/builtin/table/{tableId}/rows`
+
+| 参数 | 类型 | 必填 | 说明 |
+|------|------|------|------|
+| tableId | string | 是 | 表 ID |
+| target | string | 否 | prod/test，默认 prod |
+| primaryKeys | array | 是 | 主键数组（如 [{"id": 1}, {"id": 2}]） |
+
+**返回**：删除结果
+
+---
+
+#### 17. `export_table_excel`
+- **用途**：导出表数据为 Excel 文件
+- **对应 API**：`getBuiltinTableExportExcel(tableId, params)` ✅ 已实现 — `GET /api/datasource/connection/builtin/table/{tableId}/export/excel`
+
+| 参数 | 类型 | 必填 | 说明 |
+|------|------|------|------|
+| tableId | string | 是 | 表 ID |
+| target | string | 否 | prod/test，默认 prod |
+
+**返回**：Excel 文件（二进制 blob）+ 文件名（从 Content-Disposition 解析）
+
+---
+
+### 🔑 API 密钥与权限管理
+
+#### 18. `list_api_keys`
+- **用途**：获取 API 密钥列表
+- **对应前端**：DataSourceKeys.vue
+- **对应 API**：`getApiKeyList(data)` ✅ 已实现 — `GET /api/datasource/api_key/list`
+
+| 参数 | 类型 | 必填 | 说明 |
+|------|------|------|------|
+| apiKeyName | string | 否 | 密钥名称模糊搜索 |
+| pageNum | int | 否 | 默认 1 |
+| pageSize | int | 否 | 默认 20 |
+
+**返回**：密钥列表（名称、Key、状态、创建时间）
+
+---
+
+#### 19. `create_api_key`
+- **用途**：创建新的 API 密钥
+- **对应 API**：`postApiKey(data)` ✅ 已实现 — `POST /api/datasource/api_key`
+
+| 参数 | 类型 | 必填 | 说明 |
+|------|------|------|------|
+| apiKeyName | string | 是 | 密钥名称（最多50字） |
+
+**返回**：密钥信息（含 API Key 明文、ID）
+
+---
+
+#### 20. `toggle_api_key_status`
+- **用途**：启用/禁用 API 密钥
+- **对应 API**：`putApiKey(data)` ✅ 已实现 — `PUT /api/datasource/api_key`
+
+| 参数 | 类型 | 必填 | 说明 |
+|------|------|------|------|
+| id | string | 是 | 密钥 ID |
+| status | int | 是 | 0=启用, 1=禁用 |
+
+**返回**：操作结果
+
+---
+
+#### 21. `delete_api_key`
+- **用途**：删除 API 密钥
+- **对应 API**：`deleteApiKey(ids)` ✅ 已实现 — `DELETE /api/datasource/api_key/{ids}`
+
+| 参数 | 类型 | 必填 | 说明 |
+|------|------|------|------|
+| id | string | 是 | 密钥 ID |
+
+**返回**：删除结果
+
+---
+
+#### 22. `get_api_key_permissions`
+- **用途**：查看指定密钥的权限配置
+- **对应 API**：`getApiKeyPermission(apiKeyId)` ✅ 已实现 — `GET /api/datasource/api_key/permission/{apiKeyId}`
+
+| 参数 | 类型 | 必填 | 说明 |
+|------|------|------|------|
+| apiKeyId | string | 是 | 密钥 ID |
+
+**返回**：三级权限（connectionPermissions / databasePermissions / tablePermissions）
+
+---
+
+#### 23. `grant_api_key_permissions`
+- **用途**：批量为 API 密钥授予权限
+- **对应前端**：DataSourceKeySetting.vue
+- **对应 API**：`postApiKeyPermissionGrantBatch(data)` ✅ 已实现 — `POST /api/datasource/api_key/permission/grant_batch`
+
+| 参数 | 类型 | 必填 | 说明 |
+|------|------|------|------|
+| apiKeyId | string | 是 | 密钥 ID |
+| batchDatas | array | 是 | 权限批量数据数组 |
+| batchDatas[].connectionId | string | 是 | 数据源 ID |
+| batchDatas[].permissionLevel | string | 是 | connection/database/table |
+| batchDatas[].permissionType | string | 是 | 权限类型（逗号分隔） |
+| batchDatas[].databaseName | string | 否 | 数据库名（level=database/table 时） |
+| batchDatas[].tableName | string | 否 | 表名（level=table 时） |
+
+**返回**：授权结果
+
+---
+
+### 🤖 技能与工具管理 (内置数据源 AI 能力)
+
+#### 24. `get_skill_by_datasource`
+- **用途**：根据数据源获取技能信息
+- **对应 API**：`getSkillByDatasource(id)` ✅ 已实现 — `GET /api/datasource/skill/getByDatasource/{id}`
+
+| 参数 | 类型 | 必填 | 说明 |
+|------|------|------|------|
+| datasourceId | string | 是 | 数据源 ID |
+
+**返回**：技能信息（含 skillBool 标识）
+
+---
+
+#### 25. `get_skill_tools`
+- **用途**：获取技能下的工具列表
+- **对应 API**：`getSkillBySkillId(id)` ✅ 已实现 — `GET /api/datasource/skill/getBySkillId/{id}`
+
+| 参数 | 类型 | 必填 | 说明 |
+|------|------|------|------|
+| skillId | string | 是 | 技能 ID |
+
+**返回**：工具列表（名称、描述、SQL模板、参数定义、业务场景）
+
+---
+
+#### 26. `create_skill`
+- **用途**：为数据源创建技能
+- **对应 API**：`postSkillCreateOrGet(data)` ✅ 已实现 — `POST /api/datasource/skill/createOrGet`
+
+| 参数 | 类型 | 必填 | 说明 |
+|------|------|------|------|
+| datasourceId | string | 是 | 数据源 ID |
+| name | string | 否 | 技能名称（不传则自动生成） |
+| description | string | 否 | 技能描述 |
+
+**返回**：技能 ID
+
+---
+
+#### 27. `create_sql_tool`
+- **用途**：将 SQL 查询创建为可复用工具
+- **对应前端**：SqlControllerMsg.vue 添加到工具功能
+- **对应 API**：`postSqlSkillConfirmTools(data)` ✅ 已实现 — `POST /api/datasource/skill/confirmTools`
+
+| 参数 | 类型 | 必填 | 说明 |
+|------|------|------|------|
+| skillId | string | 是 | 技能 ID |
+| name | string | 是 | 工具名称 |
+| businessDescription | string | 是 | 业务描述 |
+| sqlTemplate | string | 是 | SQL 模板（支持 #{param} 参数占位） |
+| sqlParams | string | 否 | 参数 JSON Schema（默认空对象） |
+| resultType | string | 否 | single/list，默认 list |
+| businessScenario | string | 否 | 业务场景描述 |
+
+**返回**：工具创建结果
+
+---
+
+#### 28. `delete_skill_tool`
+- **用途**：删除技能下的工具
+- **对应 API**：`postDeleteSkillTool(skillToolId)` ✅ 已实现 — `DELETE /api/datasource/skill/tskilltool/{skillToolId}`
+
+| 参数 | 类型 | 必填 | 说明 |
+|------|------|------|------|
+| skillToolId | string | 是 | 工具 ID |
+
+**返回**：删除结果
+
+---
+
+#### 29. `update_skill_config`
+- **用途**：更新技能配置（如 MCP Server 配置模板）
+- **对应 API**：`putSkillUpdateOrGet(data)` ✅ 已实现 — `POST /api/datasource/skill/updateOrGet`
+
+| 参数 | 类型 | 必填 | 说明 |
+|------|------|------|------|
+| datasourceId | string | 是 | 数据源 ID |
+| configTemplate | string | 是 | 配置模板 JSON 字符串 |
+
+**返回**：更新结果
+
+---
+
+### 📥 数据导入
+
+#### 30. `preview_import_data`
+- **用途**：上传 Excel 文件，AI 智能识别并预览表结构/数据
+- **对应前端**：TableRecognition.vue
+- **对应 API**：`postImportDocumentPreview(connectionId, file, target)` ✅ 已实现 — `POST /api/datasource/connection/{connectionId}/import_document/preview`
+
+| 参数 | 类型 | 必填 | 说明 |
+|------|------|------|------|
+| connectionId | int | 是 | 数据源 ID |
+| target | string | 否 | prod/test，默认 test |
+| file | binary | 是 | Excel 文件 (.xlsx/.xls, <500KB) |
+
+**返回**：识别结果（表结构 + 数据预览）
+
+---
+
+#### 31. `confirm_import_data`
+- **用途**：确认导入 AI 识别后的数据
+- **对应 API**：`postImportDocumentConfirm(connectionId, data, params)` ✅ 已实现 — `POST /api/datasource/connection/{connectionId}/import_document/confirm`
+
+| 参数 | 类型 | 必填 | 说明 |
+|------|------|------|------|
+| connectionId | int | 是 | 数据源 ID |
+| target | string | 否 | prod/test |
+| data | object | 是 | 导入数据（含 tableStructure + allData） |
+
+**返回**：导入结果
+
+---
+
+### 🏷️ 表订阅
+
+#### 32. `toggle_table_subscription`
+- **用途**：切换表的订阅状态
+- **对应前端**：DatabaseDetail.vue 订阅按钮
+- **对应 API**：`postDatasourceSubscriptionToggle(data)` ✅ 已实现 — `POST /api/datasource/subscription/toggle`
+
+| 参数 | 类型 | 必填 | 说明 |
+|------|------|------|------|
+| tableId | string | 是 | 表 ID |
+| datasourceId | string | 是 | 数据源 ID |
+| subscribe | bool | 是 | true=订阅, false=取消订阅 |
+
+**返回**：操作结果
+
+---
+
+### 🔧 SQL 执行
+
+#### 33. `execute_sql`
+- **用途**：执行原生 SQL 查询
+- **对应 API**：`executeSql(data)` ✅ 已实现 — `POST /api/datasource/sqlExecutionLog/testSqlWithSchema`
+
+| 参数 | 类型 | 必填 | 说明 |
+|------|------|------|------|
+| datasourceId | string | 是 | 数据源 ID |
+| sql | string | 是 | SQL 语句 |
+| target | string | 否 | prod/test，默认 prod |
+| params | object | 否 | 参数对象 |
+
+**返回**：查询结果（表头、数据行、业务名称、描述等）
+
+---
+
+## 三、推荐使用场景
+
+### 场景 1：外部 AI Agent 管理数据库
+
+```
+用户: "帮我查一下有哪些数据源"
+Agent: 调用 list_datasources()
+
+用户: "看看 mall_db 有哪些表"
+Agent: 调用 list_tables(datasourceId="xx", databaseName="mall_db")
+
+用户: "users 表结构给我看一下"
+Agent: 调用 get_table_detail(tableId="xx")
+```
+
+### 场景 2：通过 AI 描述自动生成表结构
+
+```
+用户: "我需要一个订单系统，包含订单、订单明细、支付方式"
+Agent: 调用 generate_table_by_description(description="我需要一个订单系统...")
+Agent: 返回 AI 生成的表结构，用户确认后调用 create_table() 批量创建
+```
+
+### 场景 3：管理 API 密钥和权限
+
+```
+用户: "帮我创建一个叫'第三方报表系统'的 API Key"
+Agent: 调用 create_api_key(apiKeyName="第三方报表系统")
+
+用户: "给它开通 mall_db 数据库的读取权限"
+Agent: 调用 grant_api_key_permissions(apiKeyId="xx", batchDatas=[{...}])
+```
+
+### 场景 4：管理表数据
+
+```
+用户: "查一下 users 表前 10 条数据"
+Agent: 调用 query_table_data(tableId="xx", pageNum=1, pageSize=10)
+
+用户: "新增一个用户，用户名是 test_user"
+Agent: 调用 insert_table_row(tableId="xx", data={"user_name": "test_user", ...})
+```
+
+### 场景 5：创建 SQL 工具
+
+```
+用户: "把这个查询保存为工具，叫'按地区统计订单'"
+Agent: 调用 create_sql_tool(skillId="xx", name="按地区统计订单", 
+         sqlTemplate="SELECT region, COUNT(*) FROM orders GROUP BY region", ...)
+```
+
+### 场景 6：导入 Excel 数据
+
+```
+用户: "帮我导入这份 Excel 到测试环境"
+Agent: 调用 preview_import_data(connectionId=xx, target="test", file=...)
+Agent: 展示识别结果，用户确认后调用 confirm_import_data(...)
+```
+
+---
+
+## 四、工具优先级建议
+
+| 优先级 | 工具 | 理由 |
+|--------|------|------|
+| **P0 核心** | list_datasources, list_tables, get_table_detail, execute_sql, query_table_data | 覆盖 80% 查询场景 |
+| **P1 常用** | create_datasource, create_table, generate_table_by_description, create_api_key, grant_api_key_permissions | 管理核心操作 |
+| **P2 扩展** | insert/update/delete_table_row, export_table_excel, create_sql_tool, toggle_table_subscription | 数据操作与 AI 能力 |
+| **P3 完整** | preview/confirm_import_data, update_skill_config, alter_table, delete_skill_tool | 高级功能 |
+
+---
+
+## 五、实现建议
+
+1. **MCP Server 实现**：建议用 Python + `mcp` 库或 Node.js + `@modelcontextprotocol/sdk`
+2. **鉴权方式**：工具内部复用平台现有的 API Key 鉴权机制，调用方传入 apiKeyId
+3. **错误处理**：统一错误格式 `{ success: false, error: "描述" }`，与平台 API 拦截器保持一致
+4. **环境默认值**：所有 target 参数默认 prod，调用方显式指定 test 才能操作测试数据
+5. **批量操作**：对于 create_table 等可能涉及多表的场景，支持批量参数或循环调用
+6. **AI 工具调用**：generate_table_by_description 等 AI 工具需要调用平台的 AI 服务接口（agent generic / aiTextGenerator）
+7. **前端 API 映射**：所有 33 个 MCP 工具均已在前端 `src/server/database.ts` 中实现对应函数，可直接复用

lzwcai_mcp_agile_db/lzwcai_mcp_agile_db/数据库管理平台-功能总览.md

@@ -0,0 +1,303 @@
+# 数据库管理平台 - 功能总览
+
+> 本文档梳理 `databasePage` 组件集群与 `DatabaseDetailPage` 的整体功能架构。
+
+---
+
+## 一、系统定位
+
+这是一个面向业务用户的**数据库管理与智能问数一体化平台**，支持两种数据源模式：
+
+| 模式 | 说明 | 核心差异 |
+|------|------|----------|
+| **外部数据源** | 远程 MySQL/PostgreSQL/Oracle/SQL Server/达梦 等 | 标准数据库连接，提供只读/CRUD 管理 |
+| **内置数据源** | 平台内建 PostgreSQL 实例 | 支持 AI 技能、工具、环境切换(prod/test)、AI 训练 |
+
+---
+
+## 二、功能模块全景
+
+### 1. 数据源管理
+
+#### 1.1 数据源列表 (`DataSourceList.vue`)
+- **卡片式展示**：名称、ID、类型徽章(内置/外部)、数据库类型、运行状态、库数/表数统计
+- **无限滚动分页**：IntersectionObserver + useInfiniteScroll，每页 20 条
+- **搜索与筛选**：按名称模糊搜索、按状态筛选(运行中/已停止)
+- **数据源操作**：
+  - 编辑(外部→CreateDataSource, 内置→CreateBuiltinDataSource)
+  - 启用/停用(切换 status 0/1)
+  - 删除(运行中自动先停用再删除)
+- **业务执行入口**：点击打开智能问数聊天界面 (ChatDebugging)
+- **查看详情入口**：右侧 Drawer 打开 DatabaseDetail (95% 宽度)
+
+#### 1.2 外部数据源创建/编辑 (`CreateDataSource.vue`) - 4步向导
+| 步骤 | 内容 | 核心功能 |
+|------|------|----------|
+| Step 1 | 选择数据库类型 | MySQL/PostgreSQL/Oracle/SQL Server/达梦，自动填充默认端口 |
+| Step 2 | 配置连接信息 | 名称、描述(AI润色)、主机、端口、认证(基础认证/SSL)、用户名密码(AI生成名称)、测试连接 |
+| Step 3 | 选择数据库和表 | 树形展开、多选、搜索过滤、分页加载表列表、全选/清空 |
+| Step 4 | 确认信息 | 汇总展示已选数据库和表标签 |
+
+#### 1.3 内置数据源创建/编辑/添加表 (`CreateBuiltinDataSource.vue`)
+| 模式 | 步骤 | 说明 |
+|------|------|------|
+| create | 名称描述→业务场景→表结构 | AI 生成表结构，批量创建数据库和表 |
+| edit | 名称描述→表结构 | 更新已有内置数据源 |
+| addTable | 业务场景→表结构 | 在已有内置数据源下新增表 |
+
+- **AI 能力**：AI 优化描述、AI 生成数据库名、AI 生成表名/表描述/字段描述
+- **表结构编辑器**：左右分栏(左侧表列表, 右侧 TableDetailEditor 预览/编辑)
+- **提交流程**：创建数据源 → 创建 PostgreSQL 连接 → 创建数据库 → 批量建表 → 检查 AI 训练状态
+
+### 2. 数据库详情 (`DatabaseDetail.vue`)
+
+左侧面板 + 右侧面板的经典布局：
+
+#### 2.1 左侧 - 数据库与表管理
+- **数据库选择器**：下拉切换当前数据库，悬浮显示数据库详情(ID/名称/数据源/类型)
+- **数据表列表**：
+  - 搜索过滤
+  - 多选/全选 (Checkbox)
+  - 无限滚动加载
+  - AI 补全(选中多个表批量触发)
+  - 更多操作: AI智能建表、智能导入表、删除库
+- **底部功能按钮**：字段关联管理、AI补全管理
+
+#### 2.2 右侧 - 详情视图(三种视图)
+
+**视图 A: 表详情 (`fieldViewMode = fields`)**
+- 字段列表表格: 字段名、类型、长度、可空、主键、默认值、注释、描述
+- AI 训练状态徽章(已训练/未训练)
+- 操作: 修改表、字段关联管理、表订阅(已订阅/未订阅)、刷新
+- 用户 ID 字段关联提示(user_id/createById 等自动关联系统用户)
+
+**视图 B: 线上数据 (`fieldViewMode = online`)**
+- 通过 `CustomizeDbTable` 组件查看/编辑生产环境真实数据
+- 支持增删改查、导出 Excel、智能导入数据
+
+**视图 C: 调试数据 (`fieldViewMode = debug`)**
+- 同上，但操作测试环境数据
+
+#### 2.3 右侧 - 字段关联管理视图
+- 为当前表的字段建立与目标表字段的映射关系
+- 目标表数据更新时自动同步到当前表
+- 支持保存配置、添加/删除关联
+
+#### 2.4 右侧 - AI 补全管理视图
+- AI 补全任务列表: 任务名、类型、状态(待执行/运行中/成功/失败)、进度
+- 任务详情弹窗: 训练结果(格式化代码展示)、耗时、场景描述
+- 支持重新执行、删除任务
+
+### 3. 内建表数据管理 (`CustomizeDbTable.vue`)
+- 基于 `CommonDbTable` 的完整 CRUD 表格
+- 动态列配置: 根据表结构自动生成字段类型、宽度、可编辑性
+- **操作能力**: 新增行、编辑行、删除行、导出 Excel、导入数据、刷新
+- **导入流程**: 下载模板 → 上传 Excel → AI 识别预览 → 确认导入(调用 postImportDocumentConfirm)
+- 环境切换: `target` prop 控制 prod/test
+
+### 4. 智能导入识别 (`TableRecognition.vue`)
+- **Step 1: 上传文件**: 选择目标环境(prod/test)，上传 Excel (.xlsx/.xls, <500KB)
+- **Step 2: 智能识别**: AI 解析 Excel，预览表结构/数据，支持编辑
+- **两种模式**:
+  - `table` 模式: 根据 Excel 内容自动生成数据表结构
+  - `data` 模式: 根据规范模板识别并导入数据
+- 空行过滤、字段标记、模板下载
+
+### 5. 智能问数 / 业务执行 (`ChatDebugging.vue`)
+- **三栏布局**: 左侧面板(可折叠) + 中间聊天区 + 右侧信息
+- **左侧面板**:
+  - 数字员工列表(可收起)
+  - 新建会话按钮
+  - 会话列表(点击切换、删除)
+  - 技能列表(展开/折叠)
+    - 技能名称 + 编辑按钮
+    - 工具列表(名称、别名、编辑、删除)
+    - 至少保留一个工具
+- **中间聊天区** (`ChatBusiness` 组件):
+  - 数据源插件嵌入输入区 (`DataSourcePlugIn`)
+    - 数据库下拉选择
+    - 环境切换(生产/测试，仅内置数据源)
+  - SQL 消息控制器 (`SqlControllerMsg`)
+  - 默认数据库查询提示词(常用查询/数据统计/新手指引)
+
+#### 5.1 SQL 查询结果展示 (`SqlControllerMsg.vue`)
+| 视图类型 | 说明 |
+|----------|------|
+| SQL 代码 | 展示可执行 SQL 语句，支持复制 |
+| 图表可视化 | ChartGallery 组件渲染图表 |
+| 查询数据 | JSON 格式原始数据，支持复制 |
+| 文本说明 | 业务名称、描述、AI 解释 |
+| 表格视图 | Ant Design Table 展示查询结果 |
+| 添加到工具 | 将 SQL 查询保存为可复用工具 |
+
+- **添加工具功能**:
+  - 重复检测(按 sqlTemplate 归一化比对)
+  - 仅生产环境可用
+  - 技能创建/更新流程(无技能时自动创建 skill + MCP 配置)
+  - 通过 EventBus 触发技能刷新
+
+#### 5.2 数据源选择插件 (`DataSourcePlugIn.vue`)
+- 紧凑的内联选择器: 数据源名称 → 数据库下拉 → 环境(prod/test)
+- 监听 props 变化自动重置无效选择
+- 暴露 getSelection/clearSelection/setEnvironment 方法
+
+### 6. API 密钥管理 (`DataSourceKeys.vue` + `DataSourceKeySetting.vue`)
+- **密钥列表**: 名称、API Key(脱敏显示/可切换显示)、状态开关(启用/禁用)、创建时间、操作(详情/编辑/删除)
+- **两步创建流程**:
+  1. 输入密钥名称 → 调用 postApiKey 创建
+  2. 弹窗询问是否配置权限 → 打开权限配置
+- **权限配置** (`DataSourceKeySetting.vue`) - 3步向导:
+  - Step 1: 选择数据源(单选) + 配置数据源级权限
+  - Step 2: 选择数据库(单选, 非必填) + 配置数据库级权限
+  - Step 3: 选择数据表(多选, 非必填) + 行内配置表级权限
+  - Step 4: 完成页(ApiKeyPermissionPreview 汇总) → 批量提交权限
+- **权限选项**: 按层级不同(connection/database/table)，每种有对应的读/写/管理等权限
+- **API 调用文档**: 切换到文档视图查看调用说明
+
+### 7. 表字段编辑器 (`TableDetailEditor.vue`)
+- **表信息编辑**: 表名(AI生成)、表描述(AI优化)
+- **字段列表表格**:
+  - 序号、字段名、字段类型(分组下拉)、长度、主键、自增、可空、默认值、注释
+  - AI 生成字段描述(逐字段)
+  - 添加字段(首个字段自动设为主键+自增)
+  - 删除字段(有id的字段记录到 deletedColumns)
+  - 主键设置后不可取消(已有字段)
+  - 自增字段自动切换为整数类型
+- **两种模式**: `edit` (编辑) / `preview` (预览)
+- **校验功能**: validateFields 供外部调用
+- **字段类型** (面向 PostgreSQL): VARCHAR/TEXT/SERIAL/INTEGER/BIGINT/NUMERIC/TIMESTAMP/BOOLEAN/JSONB/INT2/INT4/INT8/SMALLINT/SMALLSERIAL/BIGSERIAL/BOOL/BIGSERIAL
+
+### 8. 其他辅助组件
+
+| 组件 | 功能 |
+|------|------|
+| `ChartGallery.vue` | 图表可视化渲染 |
+| `AddToolModal.vue` | 添加工具弹窗(工具名、描述编辑+AI辅助) |
+| `ApiKeyPermissionPreview.vue` | 权限汇总预览组件 |
+| `ApiCallDocument.vue` | API 调用文档展示 |
+| `DatabaseMessageList.vue` | 数据库消息列表 |
+| `field-types-dictionary.json` | 字段类型字典 |
+
+---
+
+## 三、API 接口层 (server/database.ts)
+
+### 数据源管理
+| 函数 | 方法 | 用途 |
+|------|------|------|
+| `getConnectionList` | GET | 数据源列表(分页+搜索+筛选) |
+| `getConnectionDetail` | GET | 数据源详情 |
+| `postConnectionDetail` | POST | 创建数据源 |
+| `putConnectionDetail` | PUT | 更新数据源 |
+| `deleteConnection` | DELETE | 删除数据源 |
+| `putConnectionChangeStatus` | PUT | 切换数据源状态(启用/停用) |
+| `testConnection` | POST | 测试连接 |
+
+### 内置数据库管理
+| 函数 | 方法 | 用途 |
+|------|------|------|
+| `postCreateBuiltinPostgreSQLConnection` | POST | 创建内置 PostgreSQL 连接 |
+| `postCreateDatabase` | POST | 创建数据库 |
+| `putAlterDatabase` | PUT | 修改数据库 |
+| `postCreateTable` | POST | 创建表 |
+| `putAlterTable` | PUT | 修改表 |
+| `postGenerateTable` | POST | AI 生成表结构 |
+| `putUpdateBuiltinDatabase` | PUT | 更新内置数据库 |
+
+### 数据库配置
+| 函数 | 方法 | 用途 |
+|------|------|------|
+| `getConnectionConfig` | GET | 获取数据库配置(含 skillBool) |
+| `getConnectionConfigList` | GET | 数据库配置列表 |
+| `postConnectionConfig` | POST | 创建数据库配置 |
+| `putConnectionConfig` | PUT | 更新数据库配置 |
+| `deleteConnectionConfig` | DELETE | 删除数据库配置 |
+| `getConnectionRealtimeStructure` | GET | 获取实时数据库结构 |
+
+### 表数据管理
+| 函数 | 方法 | 用途 |
+|------|------|------|
+| `getTableList` | GET | 表列表 |
+| `getTableDetail` | GET | 表详情 |
+| `getBuiltinTableData` | GET | 获取内置表数据(分页) |
+| `postBuiltinTableRows` | POST | 新增表数据行 |
+| `putBuiltinTableRows` | PUT | 更新表数据行 |
+| `deleteBuiltinTableRows` | DELETE | 删除表数据行 |
+| `getBuiltinTableExportExcel` | GET | 导出表数据为 Excel |
+
+### 数据导入
+| 函数 | 方法 | 用途 |
+|------|------|------|
+| `postImportDocumentPreview` | POST | 上传 Excel 预览识别结果 |
+| `postImportDocumentConfirm` | POST | 确认导入数据 |
+
+### 技能与工具
+| 函数 | 方法 | 用途 |
+|------|------|------|
+| `getSkillByDatasource` | GET | 根据数据源获取技能 |
+| `getSkillBySkillId` | GET | 根据技能ID获取工具列表 |
+| `postSkillCreateOrGet` | POST | 创建或获取技能 |
+| `putSkillUpdateOrGet` | PUT | 更新技能配置 |
+| `postSkillToolUpdateOrGet` | POST | 创建/更新技能工具 |
+| `postDeleteSkillTool` | POST | 删除技能工具 |
+| `postSqlSkillConfirmTools` | POST | 确认并创建 SQL 工具 |
+
+### AI 训练
+| 函数 | 方法 | 用途 |
+|------|------|------|
+| `getAiTrainingList` | GET | AI 训练任务列表 |
+| `postAiTrainingCreateBySelected` | POST | 创建 AI 训练任务 |
+| `getAiTrainingDetail` | GET | 训练任务详情 |
+
+### API 密钥
+| 函数 | 方法 | 用途 |
+|------|------|------|
+| `getApiKeyList` | GET | 密钥列表 |
+| `postApiKey` | POST | 创建密钥 |
+| `putApiKey` | PUT | 更新密钥 |
+| `deleteApiKey` | DELETE | 删除密钥 |
+| `getApiKeyPermission` | GET | 获取密钥权限 |
+| `postApiKeyPermissionGrantBatch` | POST | 批量授予权限 |
+
+### 订阅
+| 函数 | 方法 | 用途 |
+|------|------|------|
+| `postDatasourceSubscriptionToggle` | POST | 切换表订阅状态 |
+
+### SQL 执行
+| 函数 | 方法 | 用途 |
+|------|------|------|
+| `executeSql` | POST | 执行 SQL 查询 |
+
+---
+
+## 四、状态管理与通信
+
+- **Pinia Store**: `useDatabaseChatStore` 管理选中数据库、环境、技能状态
+- **EventBus**: `EVENTS.RELOAD_SKILL_DATA` 用于工具添加后刷新技能数据
+- **权限控制**: `hasPermission()` 函数按权限标识控制按钮可见性
+
+## 五、权限标识体系
+
+| 权限标识 | 控制范围 |
+|----------|----------|
+| `database:create` | 创建数据源 |
+| `database:edit` | 编辑数据源 |
+| `database:delete` | 删除数据源 |
+| `database:import` | 导入表/数据 |
+| `database:export` | 导出表 |
+| `database:table:create` | AI 智能建表 |
+| `database:table:ai:complete` | AI 补全功能 |
+| `database:apikey:view` | 查看密钥管理 |
+| `database:apikey:create` | 创建密钥 |
+
+---
+
+## 六、关键技术特点
+
+1. **AI 深度集成**: 描述润色、名称生成、表结构自动生成、字段描述生成、AI 补全、AI 训练
+2. **双环境隔离**: 生产/测试环境切换，测试环境限制添加工具等敏感操作
+3. **无限滚动**: IntersectionObserver + 哨兵元素实现列表分页加载
+4. **三级权限体系**: 数据源 → 数据库 → 数据表，通过 API Key 控制访问粒度
+5. **MCP 工具集成**: 内置数据源自动配置 MCP Server (`lzwcai-mcp-sqlexecutor`)，支持 AI 工具注册
+6. **Excel 智能导入**: AI 识别 Excel 内容，自动匹配表结构，支持表结构和数据两种导入模式

lzwcai_mcp_agile_db/main.py

@@ -0,0 +1,12 @@
+"""
+Entry point for lzwcai-mcp-agile-db
+Runs the MCP server for database management platform
+"""
+
+from lzwcai_mcp_agile_db.server import main
+import os
+
+if __name__ == "__main__":
+    os.environ["AGILE_DB_API_KEY"] = "Bearer eyJhbGciOiJIUzUxMiJ9.eyJ0b2tlbl90eXBlIjoiTE9HSU4iLCJsb2dpbl91c2VyX2tleSI6IjJiMDY0YzMzLTBiZWYtNDU0NC04NWY1LTRmNTFiOGMxMmI5NSJ9.Uv599TvlQvlTlwrnZGo3Tl2eLAvM0ldE9vpMI5jHxbTf4_tVSRA60rUNIV4LBiw6pt1r_xIi7aFcTRE2PeN5sg"
+    os.environ["AGILE_DB_BASE_URL"] = "https://dempdemo.lzwcai.com"
+    main()

lzwcai_mcp_agile_db/pyproject.toml

@@ -0,0 +1,34 @@
+[build-system]
+requires = ["hatchling"]
+build-backend = "hatchling.build"
+
+[project]
+name = "lzwcai-mcp-agile-db"
+version = "0.1.0"
+description = "MCP server for database management platform with 33 tools for datasource, table, data, API key, and skill management"
+readme = "README.md"
+requires-python = ">=3.10"
+license = {text = "MIT"}
+authors = [
+    {name = "lzwcai", email = "your-email@example.com"},
+]
+keywords = ["mcp", "database", "agile", "server"]
+classifiers = [
+    "Development Status :: 3 - Alpha",
+    "Intended Audience :: Developers",
+    "Programming Language :: Python :: 3",
+    "Programming Language :: Python :: 3.10",
+    "Programming Language :: Python :: 3.11",
+    "Programming Language :: Python :: 3.12",
+    "Programming Language :: Python :: 3.13",
+]
+dependencies = [
+    "httpx>=0.28.1",
+    "mcp[cli]>=1.10.1",
+]
+
+[project.scripts]
+lzwcai-mcp-agile-db = "lzwcai_mcp_agile_db.server:main"
+
+[tool.hatch.build.targets.wheel]
+packages = ["lzwcai_mcp_agile_db"]

lzwcai_mcp_sqlexecutor/lzwcai_mcp_sqlexecutor/logs/lzwcai_mcp_sqlexecutor_daily.log

@@ -1,25 +1,289 @@
-2026-05-25 14:32:22 - root - INFO - [logger_config.py:151] - 日志系统初始化完成 - 日志目录: E:\yh-ai\project\lzwcai-szyg\lzwcai-mcp-server-package\lzwcai_mcp_sqlexecutor\lzwcai_mcp_sqlexecutor\logs
+2026-05-25 16:05:46 - root - INFO - [logger_config.py:151] - 日志系统初始化完成 - 日志目录: E:\yh-ai\project\lzwcai-szyg\lzwcai-mcp-server-package\lzwcai_mcp_sqlexecutor\lzwcai_mcp_sqlexecutor\logs
-2026-05-25 14:32:22 - root - INFO - [logger_config.py:152] - 日志配置 - 级别: INFO, 文件大小限制: 10MB, 备份数量: 5
+2026-05-25 16:05:46 - root - INFO - [logger_config.py:152] - 日志配置 - 级别: INFO, 文件大小限制: 10MB, 备份数量: 5
-2026-05-25 14:32:22 - mcp_services - INFO - [main.py:352] - 开始运行 MCP SQL Executor 服务器
+2026-05-25 16:05:46 - mcp_services - INFO - [main.py:352] - 开始运行 MCP SQL Executor 服务器
-2026-05-25 14:32:22 - mcp_services - INFO - [main.py:304] - ============================================================
+2026-05-25 16:05:46 - mcp_services - INFO - [main.py:304] - ============================================================
-2026-05-25 14:32:22 - mcp_services - INFO - [main.py:305] - 正在启动 MCP 服务器: lzwcai-mcp-sqlexecutor
+2026-05-25 16:05:46 - mcp_services - INFO - [main.py:305] - 正在启动 MCP 服务器: lzwcai-mcp-sqlexecutor
-2026-05-25 14:32:22 - mcp_services - INFO - [main.py:306] - 版本: 0.1.0
+2026-05-25 16:05:46 - mcp_services - INFO - [main.py:306] - 版本: 0.1.0
-2026-05-25 14:32:22 - mcp_services - INFO - [main.py:307] - ============================================================
+2026-05-25 16:05:46 - mcp_services - INFO - [main.py:307] - ============================================================
-2026-05-25 14:32:22 - mcp_services - INFO - [main.py:311] - 环境配置 - Database ID: 162
+2026-05-25 16:05:46 - mcp_services - INFO - [main.py:311] - 环境配置 - Database ID: 240
-2026-05-25 14:32:22 - mcp_services - INFO - [main.py:312] - 环境配置 - Skill ID: 2008360664955854850
+2026-05-25 16:05:46 - mcp_services - INFO - [main.py:312] - 环境配置 - Skill ID: 2058819964077572098
-2026-05-25 14:32:22 - mcp_services - INFO - [main.py:313] - 环境配置 - Backend Base URL: http://192.168.2.236:8088
+2026-05-25 16:05:46 - mcp_services - INFO - [main.py:313] - 环境配置 - Backend Base URL: http://192.168.2.236:8088
-2026-05-25 14:32:22 - mcp_services - INFO - [main.py:314] - ============================================================
+2026-05-25 16:05:46 - mcp_services - INFO - [main.py:314] - ============================================================
-2026-05-25 14:32:22 - mcp_services - INFO - [main.py:319] - MCP 服务器已启动，等待客户端连接...
+2026-05-25 16:05:46 - mcp_services - INFO - [main.py:319] - MCP 服务器已启动，等待客户端连接...
-2026-05-25 14:32:35 - mcp.server.lowlevel.server - INFO - [server.py:720] - Processing request of type ListToolsRequest
+2026-05-25 16:05:49 - mcp.server.lowlevel.server - INFO - [server.py:720] - Processing request of type ListToolsRequest
-2026-05-25 14:32:35 - mcp_services - INFO - [main.py:156] - 收到列出工具请求
+2026-05-25 16:05:49 - mcp_services - INFO - [main.py:156] - 收到列出工具请求
-2026-05-25 14:32:35 - mcp_services - INFO - [main.py:119] - 初始化查询配置（数据源: api）...
+2026-05-25 16:05:49 - mcp_services - INFO - [main.py:119] - 初始化查询配置（数据源: api）...
-2026-05-25 14:32:35 - mcp_services - INFO - [main.py:283] - 调用第三方API，skill_id: 2008360664955854850
+2026-05-25 16:05:49 - mcp_services - INFO - [main.py:283] - 调用第三方API，skill_id: 2058819964077572098
-2026-05-25 14:32:35 - lzwcai_mcp_sqlexecutor.utils.api_client - INFO - [api_client.py:71] - 正在调用API: http://192.168.2.236:8088/datasource/skill/getBySkillId/2008360664955854850
+2026-05-25 16:05:49 - lzwcai_mcp_sqlexecutor.utils.api_client - INFO - [api_client.py:71] - 正在调用API: http://192.168.2.236:8088/datasource/skill/getBySkillId/2058819964077572098
-2026-05-25 14:32:35 - httpx - INFO - [_client.py:1025] - HTTP Request: GET http://192.168.2.236:8088/datasource/skill/getBySkillId/2008360664955854850 "HTTP/1.1 200 "
+2026-05-25 16:05:49 - httpx - INFO - [_client.py:1025] - HTTP Request: GET http://192.168.2.236:8088/datasource/skill/getBySkillId/2058819964077572098 "HTTP/1.1 200 "
-2026-05-25 14:32:35 - lzwcai_mcp_sqlexecutor.utils.api_client - INFO - [api_client.py:85] - API调用成功: http://192.168.2.236:8088/datasource/skill/getBySkillId/2008360664955854850
+2026-05-25 16:05:49 - lzwcai_mcp_sqlexecutor.utils.api_client - INFO - [api_client.py:85] - API调用成功: http://192.168.2.236:8088/datasource/skill/getBySkillId/2058819964077572098
-2026-05-25 14:32:35 - mcp_services - INFO - [main.py:288] - 成功{'msg': '查询成功', 'code': 200, 'data': [{'id': '2008360824029028354', 'createBy': 'wxl06', 'createTime': '2026-01-06 10:11:49', 'updateBy': 'wxl06', 'updateTime': '2026-01-06 10:11:59', 'serviceId': '2008360664960049153', 'uniqueName': '查询订单信息', 'name': 'chaxundingdanxinxi_3acda9b4', 'description': 'chaxundingdanxinxi_3acda9b4: 查询订单表中的订单信息，包括订单号、产品名称、数量、购买客户、备注和状态等关键信息', 'visualizable': 1, 'toolPrompt': '查询成功，返回 6 行数据，执行时间: 4ms', 'toolType': 'sql', 'datasourceId': '162', 'sqlTemplate': 'SELECT order_id, product_name, quantity, customer, remarks, status FROM orders WHERE 1=1', 'sqlParams': '{"type":"object","required":[],"properties":{}}', 'resultType': 'list', 'sourceType': 'ai', 'trainingTaskId': None, 'tableMetadataIds': '', 'executionCount': 0, 'visualizationConfigs': None, 'inputJsonSchema': '{"type":"object","required":["employeeId"],"properties":{"employeeId":{"type":"number","description":"员工ID，用于标识员工的唯一数字标识符","examples":[1001,2002]},"targetDatabaseName":{"type":"string","description":"目标数据库名称"}}}', 'outputJsonSchema': '{"type":"object","properties":{"data":{"type":"array"}}}', 'lastExecutionTime': None}]}
+2026-05-25 16:05:49 - mcp_services - INFO - [main.py:288] - 成功{'msg': '查询成功', 'code': 200, 'data': [{'id': '2058819964287287298', 'createBy': 'wxl06', 'createTime': '2026-05-25 15:58:25', 'updateBy': None, 'updateTime': None, 'serviceId': '2058819964085960705', 'uniqueName': '前50条导入数据明细查询', 'name': 'qian50tiaodaorushujumingxichaxun_32b1d628', 'description': 'qian50tiaodaorushujumingxichaxun_32b1d628: qian50tiaodaorushujumingxichaxun_32b1d628: qian50tiaodaorushujumingxichaxun_32b1d628: qian50tiaodaorushujumingxichaxun_32b1d628: 查询数据导入明细表中的前50条记录，包含原始数据、处理状态、错误原因等关键信息，用于快速预览最近的导入情况。', 'visualizable': 1, 'toolPrompt': '查询成功，返回 6 行数据，执行时间: 1ms', 'toolType': 'sql', 'datasourceId': '240', 'sqlTemplate': 'SELECT record_id AS "记录ID", task_id AS "任务ID", original_data AS "原始数据", process_result AS "处理结果", error_reason AS "错误原因", process_status AS "处理状态", target_table AS "关联目标表", created_time AS "创建时间" FROM import_record_detail LIMIT 50;', 'sqlParams': '{}', 'resultType': 'list', 'sourceType': 'ai', 'trainingTaskId': None, 'tableMetadataIds': '', 'executionCount': 0, 'visualizationConfigs': None, 'inputJsonSchema': '{"type":"object","properties":{},"required":[]}', 'outputJsonSchema': '{"type":"object","properties":{"text":{"type":"string"}},"additionalProperties":false}', 'lastExecutionTime': None}]}
-2026-05-25 14:32:35 - lzwcai_mcp_sqlexecutor.utils.api_client - INFO - [api_client.py:324] - 成功处理 1 条技能数据
+2026-05-25 16:05:49 - lzwcai_mcp_sqlexecutor.utils.api_client - INFO - [api_client.py:324] - 成功处理 1 条技能数据
-2026-05-25 14:32:35 - mcp_services - INFO - [main.py:293] - 成功获取并处理 1 条数据
+2026-05-25 16:05:49 - mcp_services - INFO - [main.py:293] - 成功获取并处理 1 条数据
-2026-05-25 14:32:35 - mcp_services - INFO - [main.py:128] - API配置: 1 条
+2026-05-25 16:05:49 - mcp_services - INFO - [main.py:128] - API配置: 1 条
-2026-05-25 14:32:35 - mcp_services - INFO - [main.py:129] - API配置数组: [{'id': '2008360824029028354', 'businessName': 'chaxundingdanxinxi_3acda9b4', 'businessDescription': 'chaxundingdanxinxi_3acda9b4: 查询订单表中的订单信息，包括订单号、产品名称、数量、购买客户、备注和状态等关键信息', 'sqlTemplate': 'SELECT order_id, product_name, quantity, customer, remarks, status FROM orders WHERE 1=1', 'parameters': {'type': 'object', 'required': [], 'properties': {}}, 'datasourceId': '162'}]
+2026-05-25 16:05:49 - mcp_services - INFO - [main.py:129] - API配置数组: [{'id': '2058819964287287298', 'businessName': 'qian50tiaodaorushujumingxichaxun_32b1d628', 'businessDescription': 'qian50tiaodaorushujumingxichaxun_32b1d628: qian50tiaodaorushujumingxichaxun_32b1d628: qian50tiaodaorushujumingxichaxun_32b1d628: qian50tiaodaorushujumingxichaxun_32b1d628: 查询数据导入明细表中的前50条记录，包含原始数据、处理状态、错误原因等关键信息，用于快速预览最近的导入情况。', 'sqlTemplate': 'SELECT record_id AS "记录ID", task_id AS "任务ID", original_data AS "原始数据", process_result AS "处理结果", error_reason AS "错误原因", process_status AS "处理状态", target_table AS "关联目标表", created_time AS "创建时间" FROM import_record_detail LIMIT 50;', 'parameters': {}, 'datasourceId': '240'}]
-2026-05-25 14:32:35 - mcp_services - INFO - [main.py:165] - 成功生成 1 个 MCP 工具
+2026-05-25 16:05:49 - mcp_services - INFO - [main.py:165] - 成功生成 1 个 MCP 工具
+2026-05-25 16:05:52 - mcp.server.lowlevel.server - INFO - [server.py:720] - Processing request of type CallToolRequest
+2026-05-25 16:05:52 - mcp_services - INFO - [main.py:190] - 收到工具调用请求: qian50tiaodaorushujumingxichaxun_32b1d628
+2026-05-25 16:05:52 - mcp_services - INFO - [main.py:230] - 正在调用测试SQL API...
+2026-05-25 16:05:52 - lzwcai_mcp_sqlexecutor.utils.api_client - INFO - [api_client.py:132] - ================================================================================
+2026-05-25 16:05:52 - lzwcai_mcp_sqlexecutor.utils.api_client - INFO - [api_client.py:133] - test_sql_with_schema 接口接收到的数据:
+2026-05-25 16:05:52 - lzwcai_mcp_sqlexecutor.utils.api_client - INFO - [api_client.py:134] - 数据类型: <class 'dict'>
+2026-05-25 16:05:52 - lzwcai_mcp_sqlexecutor.utils.api_client - INFO - [api_client.py:135] - 数据内容: {
+  "datasourceId": "240",
+  "businessName": "qian50tiaodaorushujumingxichaxun_32b1d628",
+  "businessDescription": "qian50tiaodaorushujumingxichaxun_32b1d628: qian50tiaodaorushujumingxichaxun_32b1d628: qian50tiaodaorushujumingxichaxun_32b1d628: qian50tiaodaorushujumingxichaxun_32b1d628: 查询数据导入明细表中的前50条记录，包含原始数据、处理状态、错误原因等关键信息，用于快速预览最近的导入情况。",
+  "sqlTemplate": "SELECT record_id AS \"记录ID\", task_id AS \"任务ID\", original_data AS \"原始数据\", process_result AS \"处理结果\", error_reason AS \"错误原因\", process_status AS \"处理状态\", target_table AS \"关联目标表\", created_time AS \"创建时间\" FROM import_record_detail LIMIT 50;",
+  "parameters": {},
+  "testParams": {}
+}
+2026-05-25 16:05:52 - lzwcai_mcp_sqlexecutor.utils.api_client - INFO - [api_client.py:136] - 数据源ID: 240
+2026-05-25 16:05:52 - lzwcai_mcp_sqlexecutor.utils.api_client - INFO - [api_client.py:137] - 业务名称: qian50tiaodaorushujumingxichaxun_32b1d628
+2026-05-25 16:05:52 - lzwcai_mcp_sqlexecutor.utils.api_client - INFO - [api_client.py:138] - 业务描述: qian50tiaodaorushujumingxichaxun_32b1d628: qian50tiaodaorushujumingxichaxun_32b1d628: qian50tiaodaorushujumingxichaxun_32b1d628: qian50tiaodaorushujumingxichaxun_32b1d628: 查询数据导入明细表中的前50条记录，包含原始数据、处理状态、错误原因等关键信息，用于快速预览最近的导入情况。
+2026-05-25 16:05:52 - lzwcai_mcp_sqlexecutor.utils.api_client - INFO - [api_client.py:139] - SQL模板: SELECT record_id AS "记录ID", task_id AS "任务ID", original_data AS "原始数据", process_result AS "处理结果", error_reason AS "错误原因", process_status AS "处理状态", target_table AS "关联目标表", created_time AS "创建时间" FROM import_record_detail LIMIT 50;
+2026-05-25 16:05:52 - lzwcai_mcp_sqlexecutor.utils.api_client - INFO - [api_client.py:140] - 参数定义: {}
+2026-05-25 16:05:52 - lzwcai_mcp_sqlexecutor.utils.api_client - INFO - [api_client.py:141] - 测试参数: {}
+2026-05-25 16:05:52 - lzwcai_mcp_sqlexecutor.utils.api_client - INFO - [api_client.py:144] - ================================================================================
+2026-05-25 16:05:52 - lzwcai_mcp_sqlexecutor.utils.api_client - INFO - [api_client.py:153] - 正在调用测试SQL API: http://192.168.2.236:8088/datasource/sqlExecutionLog/testSqlWithSchema
+2026-05-25 16:05:52 - httpx - INFO - [_client.py:1025] - HTTP Request: POST http://192.168.2.236:8088/datasource/sqlExecutionLog/testSqlWithSchema "HTTP/1.1 200 "
+2026-05-25 16:05:52 - lzwcai_mcp_sqlexecutor.utils.api_client - INFO - [api_client.py:170] - ================================================================================
+2026-05-25 16:05:52 - lzwcai_mcp_sqlexecutor.utils.api_client - INFO - [api_client.py:171] - test_sql_with_schema 接口返回的数据:
+2026-05-25 16:05:52 - lzwcai_mcp_sqlexecutor.utils.api_client - INFO - [api_client.py:172] - HTTP状态码: 200
+2026-05-25 16:05:52 - lzwcai_mcp_sqlexecutor.utils.api_client - INFO - [api_client.py:173] - 响应数据类型: <class 'dict'>
+2026-05-25 16:05:52 - lzwcai_mcp_sqlexecutor.utils.api_client - INFO - [api_client.py:174] - 响应数据内容: {
+  "msg": "操作成功",
+  "code": 200,
+  "data": {
+    "resultCount": 6,
+    "data": [
+      {
+        "记录ID": 80001,
+        "任务ID": "3320260418001",
+        "原始数据": "{\"name\": \"张三\", \"mobile\": \"13800000101\", \"dept\": \"销售部\", \"amount\": 1200}",
+        "处理结果": "导入成功",
+        "错误原因": null,
+        "处理状态": "SUCCESS",
+        "关联目标表": "employee_import",
+        "创建时间": "2026-04-18T15:19:19.000+08:00"
+      },
+      {
+        "记录ID": 80002,
+        "任务ID": "3320260418002",
+        "原始数据": "{\"name\": \"李四\", \"mobile\": \"13800000102\", \"dept\": \"财务部\", \"amount\": 980}",
+        "处理结果": "导入成功",
+        "错误原因": null,
+        "处理状态": "SUCCESS",
+        "关联目标表": "employee_import",
+        "创建时间": "2026-04-18T15:19:34.000+08:00"
+      },
+      {
+        "记录ID": 80003,
+        "任务ID": "3320260418003",
+        "原始数据": "{\"name\": \"王五\", \"mobile\": \"13800000103\", \"dept\": \"技术部\", \"amount\": 1500}",
+        "处理结果": "导入失败",
+        "错误原因": "字段校验失败：mobile格式不正确",
+        "处理状态": "FAILED",
+        "关联目标表": "employee_import",
+        "创建时间": "2026-04-18T15:19:49.000+08:00"
+      },
+      {
+        "记录ID": 80004,
+        "任务ID": "3320260418004",
+        "原始数据": "{\"name\": \"赵六\", \"mobile\": \"13800000104\", \"dept\": \"人事部\", \"amount\": 0}",
+        "处理结果": "导入成功",
+        "错误原因": null,
+        "处理状态": "SUCCESS",
+        "关联目标表": "employee_import",
+        "创建时间": "2026-04-18T15:20:04.000+08:00"
+      },
+      {
+        "记录ID": 80005,
+        "任务ID": "3320260418005",
+        "原始数据": "{\"name\": \"孙七\", \"mobile\": \"13800000105\", \"dept\": \"运营部\", \"amount\": 2000}",
+        "处理结果": "导入失败",
+        "错误原因": "目标表写入失败：唯一键冲突",
+        "处理状态": "FAILED",
+        "关联目标表": "employee_import",
+        "创建时间": "2026-04-18T15:20:19.000+08:00"
+      },
+      {
+        "记录ID": 80006,
+        "任务ID": "3320260418006",
+        "原始数据": "{\"name\": \"周八\", \"mobile\": \"13800000106\", \"dept\": \"法务部\", \"amount\": 300}",
+        "处理结果": "导入成功",
+        "错误原因": null,
+        "处理状态": "SUCCESS",
+        "关联目标表": "employee_import",
+        "创建时间": "2026-04-18T15:20:34.000+08:00"
+      }
+    ],
+    "databaseName": "import_log_db_168",
+    "businessDescription": "qian50tiaodaorushujumingxichaxun_32b1d628: qian50tiaodaorushujumingxichaxun_32b1d628: qian50tiaodaorushujumingxichaxun_32b1d628: qian50tiaodaorushujumingxichaxun_32b1d628: 查询数据导入明细表中的前50条记录，包含原始数据、处理状态、错误原因等关键信息，用于快速预览最近的导入情况。",
+    "originalTemplate": "SELECT record_id AS \"记录ID\", task_id AS \"任务ID\", original_data AS \"原始数据\", process_result AS \"处理结果\", error_reason AS \"错误原因\", process_status AS \"处理状态\", target_table AS \"关联目标表\", created_time AS \"创建时间\" FROM import_record_detail LIMIT 50;",
+    "convertedTemplate": "SELECT record_id AS \"记录ID\", task_id AS \"任务ID\", original_data AS \"原始数据\", process_result AS \"处理结果\", error_reason AS \"错误原因\", process_status AS \"处理状态\", target_table AS \"关联目标表\", created_time AS \"创建时间\" FROM import_record_detail LIMIT 50;",
+    "executionStatus": "success",
+    "businessName": "qian50tiaodaorushujumingxichaxun_32b1d628",
+    "testParams": {},
+    "errorMessage": null,
+    "executionTime": 8,
+    "datasourceId": "240",
+    "logId": "2058821884796174336",
+    "executableSql": "SELECT record_id AS \"记录ID\", task_id AS \"任务ID\", original_data AS \"原始数据\", process_result AS \"处理结果\", error_reason AS \"错误原因\", process_status AS \"处理状态\", target_table AS \"关联目标表\", created_time AS \"创建时间\" FROM import_record_detail LIMIT 50;",
+    "datasourceName": "import_log_db_168"
+  }
+}
+2026-05-25 16:05:52 - lzwcai_mcp_sqlexecutor.utils.api_client - INFO - [api_client.py:176] - 响应code: 200
+2026-05-25 16:05:52 - lzwcai_mcp_sqlexecutor.utils.api_client - INFO - [api_client.py:177] - 响应msg: 操作成功
+2026-05-25 16:05:52 - lzwcai_mcp_sqlexecutor.utils.api_client - INFO - [api_client.py:178] - 响应data: {'resultCount': 6, 'data': [{'记录ID': 80001, '任务ID': '3320260418001', '原始数据': '{"name": "张三", "mobile": "13800000101", "dept": "销售部", "amount": 1200}', '处理结果': '导入成功', '错误原因': None, '处理状态': 'SUCCESS', '关联目标表': 'employee_import', '创建时间': '2026-04-18T15:19:19.000+08:00'}, {'记录ID': 80002, '任务ID': '3320260418002', '原始数据': '{"name": "李四", "mobile": "13800000102", "dept": "财务部", "amount": 980}', '处理结果': '导入成功', '错误原因': None, '处理状态': 'SUCCESS', '关联目标表': 'employee_import', '创建时间': '2026-04-18T15:19:34.000+08:00'}, {'记录ID': 80003, '任务ID': '3320260418003', '原始数据': '{"name": "王五", "mobile": "13800000103", "dept": "技术部", "amount": 1500}', '处理结果': '导入失败', '错误原因': '字段校验失败：mobile格式不正确', '处理状态': 'FAILED', '关联目标表': 'employee_import', '创建时间': '2026-04-18T15:19:49.000+08:00'}, {'记录ID': 80004, '任务ID': '3320260418004', '原始数据': '{"name": "赵六", "mobile": "13800000104", "dept": "人事部", "amount": 0}', '处理结果': '导入成功', '错误原因': None, '处理状态': 'SUCCESS', '关联目标表': 'employee_import', '创建时间': '2026-04-18T15:20:04.000+08:00'}, {'记录ID': 80005, '任务ID': '3320260418005', '原始数据': '{"name": "孙七", "mobile": "13800000105", "dept": "运营部", "amount": 2000}', '处理结果': '导入失败', '错误原因': '目标表写入失败：唯一键冲突', '处理状态': 'FAILED', '关联目标表': 'employee_import', '创建时间': '2026-04-18T15:20:19.000+08:00'}, {'记录ID': 80006, '任务ID': '3320260418006', '原始数据': '{"name": "周八", "mobile": "13800000106", "dept": "法务部", "amount": 300}', '处理结果': '导入成功', '错误原因': None, '处理状态': 'SUCCESS', '关联目标表': 'employee_import', '创建时间': '2026-04-18T15:20:34.000+08:00'}], 'databaseName': 'import_log_db_168', 'businessDescription': 'qian50tiaodaorushujumingxichaxun_32b1d628: qian50tiaodaorushujumingxichaxun_32b1d628: qian50tiaodaorushujumingxichaxun_32b1d628: qian50tiaodaorushujumingxichaxun_32b1d628: 查询数据导入明细表中的前50条记录，包含原始数据、处理状态、错误原因等关键信息，用于快速预览最近的导入情况。', 'originalTemplate': 'SELECT record_id AS "记录ID", task_id AS "任务ID", original_data AS "原始数据", process_result AS "处理结果", error_reason AS "错误原因", process_status AS "处理状态", target_table AS "关联目标表", created_time AS "创建时间" FROM import_record_detail LIMIT 50;', 'convertedTemplate': 'SELECT record_id AS "记录ID", task_id AS "任务ID", original_data AS "原始数据", process_result AS "处理结果", error_reason AS "错误原因", process_status AS "处理状态", target_table AS "关联目标表", created_time AS "创建时间" FROM import_record_detail LIMIT 50;', 'executionStatus': 'success', 'businessName': 'qian50tiaodaorushujumingxichaxun_32b1d628', 'testParams': {}, 'errorMessage': None, 'executionTime': 8, 'datasourceId': '240', 'logId': '2058821884796174336', 'executableSql': 'SELECT record_id AS "记录ID", task_id AS "任务ID", original_data AS "原始数据", process_result AS "处理结果", error_reason AS "错误原因", process_status AS "处理状态", target_table AS "关联目标表", created_time AS "创建时间" FROM import_record_detail LIMIT 50;', 'datasourceName': 'import_log_db_168'}
+2026-05-25 16:05:52 - lzwcai_mcp_sqlexecutor.utils.api_client - INFO - [api_client.py:179] - ================================================================================
+2026-05-25 16:05:52 - lzwcai_mcp_sqlexecutor.utils.api_client - INFO - [api_client.py:181] - 测试SQL API调用成功
+2026-05-25 16:05:52 - mcp_services - INFO - [main.py:232] - 测试SQL API调用成功
+2026-05-25 16:15:08 - root - INFO - [logger_config.py:151] - 日志系统初始化完成 - 日志目录: E:\yh-ai\project\lzwcai-szyg\lzwcai-mcp-server-package\lzwcai_mcp_sqlexecutor\lzwcai_mcp_sqlexecutor\logs
+2026-05-25 16:15:08 - root - INFO - [logger_config.py:152] - 日志配置 - 级别: INFO, 文件大小限制: 10MB, 备份数量: 5
+2026-05-25 16:15:08 - mcp_services - INFO - [main.py:246] - 开始运行 MCP SQL Executor 服务
+2026-05-25 16:15:08 - mcp_services - INFO - [main.py:204] - ============================================================
+2026-05-25 16:15:08 - mcp_services - INFO - [main.py:205] - 正在启动 MCP 服务: lzwcai-mcp-sqlexecutor
+2026-05-25 16:15:08 - mcp_services - INFO - [main.py:206] - 版本: 0.1.0
+2026-05-25 16:15:08 - mcp_services - INFO - [main.py:207] - ============================================================
+2026-05-25 16:15:08 - mcp_services - INFO - [main.py:210] - 环境配置 - Database ID: 240
+2026-05-25 16:15:08 - mcp_services - INFO - [main.py:211] - 环境配置 - Skill ID: 2058819964077572098
+2026-05-25 16:15:08 - mcp_services - INFO - [main.py:212] - 环境配置 - Backend Base URL: http://192.168.2.236:8088
+2026-05-25 16:15:08 - mcp_services - INFO - [main.py:213] - ============================================================
+2026-05-25 16:15:08 - mcp_services - INFO - [main.py:218] - MCP 服务已启动，等待客户端连接...
+2026-05-25 16:15:09 - mcp.server.lowlevel.server - INFO - [server.py:720] - Processing request of type ListToolsRequest
+2026-05-25 16:15:09 - mcp_services - INFO - [main.py:107] - 收到列出工具请求
+2026-05-25 16:15:09 - mcp_services - INFO - [main.py:77] - 初始化查询配置，数据源: api
+2026-05-25 16:15:09 - mcp_services - INFO - [main.py:189] - 调用第三方 API，skill_id: 2058819964077572098
+2026-05-25 16:15:09 - lzwcai_mcp_sqlexecutor.utils.api_client - INFO - [api_client.py:71] - 正在调用API: http://192.168.2.236:8088/datasource/skill/getBySkillId/2058819964077572098
+2026-05-25 16:15:09 - httpx - INFO - [_client.py:1025] - HTTP Request: GET http://192.168.2.236:8088/datasource/skill/getBySkillId/2058819964077572098 "HTTP/1.1 200 "
+2026-05-25 16:15:09 - lzwcai_mcp_sqlexecutor.utils.api_client - INFO - [api_client.py:85] - API调用成功: http://192.168.2.236:8088/datasource/skill/getBySkillId/2058819964077572098
+2026-05-25 16:15:09 - mcp_services - INFO - [main.py:191] - 成功获取原始响应: {'msg': '查询成功', 'code': 200, 'data': [{'id': '2058819964287287298', 'createBy': 'wxl06', 'createTime': '2026-05-25 15:58:25', 'updateBy': None, 'updateTime': None, 'serviceId': '2058819964085960705', 'uniqueName': '前50条导入数据明细查询', 'name': 'qian50tiaodaorushujumingxichaxun_32b1d628', 'description': 'qian50tiaodaorushujumingxichaxun_32b1d628: qian50tiaodaorushujumingxichaxun_32b1d628: qian50tiaodaorushujumingxichaxun_32b1d628: qian50tiaodaorushujumingxichaxun_32b1d628: 查询数据导入明细表中的前50条记录，包含原始数据、处理状态、错误原因等关键信息，用于快速预览最近的导入情况。', 'visualizable': 1, 'toolPrompt': '查询成功，返回 6 行数据，执行时间: 1ms', 'toolType': 'sql', 'datasourceId': '240', 'sqlTemplate': 'SELECT record_id AS "记录ID", task_id AS "任务ID", original_data AS "原始数据", process_result AS "处理结果", error_reason AS "错误原因", process_status AS "处理状态", target_table AS "关联目标表", created_time AS "创建时间" FROM import_record_detail LIMIT 50;', 'sqlParams': '{}', 'resultType': 'list', 'sourceType': 'ai', 'trainingTaskId': None, 'tableMetadataIds': '', 'executionCount': 0, 'visualizationConfigs': None, 'inputJsonSchema': '{"type":"object","properties":{},"required":[]}', 'outputJsonSchema': '{"type":"object","properties":{"text":{"type":"string"}},"additionalProperties":false}', 'lastExecutionTime': None}]}
+2026-05-25 16:15:09 - lzwcai_mcp_sqlexecutor.utils.api_client - INFO - [api_client.py:325] - 成功处理 1 条技能数据
+2026-05-25 16:15:09 - mcp_services - INFO - [main.py:194] - 成功处理 1 条数据
+2026-05-25 16:15:09 - mcp_services - INFO - [main.py:85] - API 配置: 1 条
+2026-05-25 16:15:09 - mcp_services - INFO - [main.py:86] - API 配置数组: [{'id': '2058819964287287298', 'businessName': 'qian50tiaodaorushujumingxichaxun_32b1d628', 'businessDescription': 'qian50tiaodaorushujumingxichaxun_32b1d628: qian50tiaodaorushujumingxichaxun_32b1d628: qian50tiaodaorushujumingxichaxun_32b1d628: qian50tiaodaorushujumingxichaxun_32b1d628: 查询数据导入明细表中的前50条记录，包含原始数据、处理状态、错误原因等关键信息，用于快速预览最近的导入情况。', 'sqlTemplate': 'SELECT record_id AS "记录ID", task_id AS "任务ID", original_data AS "原始数据", process_result AS "处理结果", error_reason AS "错误原因", process_status AS "处理状态", target_table AS "关联目标表", created_time AS "创建时间" FROM import_record_detail LIMIT 50;', 'parameters': {}, 'datasourceId': '240'}]
+2026-05-25 16:15:09 - mcp_services - INFO - [main.py:110] - 成功生成 1 个 MCP 工具
+2026-05-25 16:22:48 - root - INFO - [logger_config.py:151] - 日志系统初始化完成 - 日志目录: E:\yh-ai\project\lzwcai-szyg\lzwcai-mcp-server-package\lzwcai_mcp_sqlexecutor\lzwcai_mcp_sqlexecutor\logs
+2026-05-25 16:22:48 - root - INFO - [logger_config.py:152] - 日志配置 - 级别: INFO, 文件大小限制: 10MB, 备份数量: 5
+2026-05-25 16:22:48 - mcp_services - INFO - [main.py:258] - 开始运行 MCP SQL Executor 服务
+2026-05-25 16:22:48 - mcp_services - INFO - [main.py:216] - ============================================================
+2026-05-25 16:22:48 - mcp_services - INFO - [main.py:217] - 正在启动 MCP 服务: lzwcai-mcp-sqlexecutor
+2026-05-25 16:22:48 - mcp_services - INFO - [main.py:218] - 版本: 0.1.0
+2026-05-25 16:22:48 - mcp_services - INFO - [main.py:219] - ============================================================
+2026-05-25 16:22:48 - mcp_services - INFO - [main.py:222] - 环境配置 - Database ID: 29
+2026-05-25 16:22:48 - mcp_services - INFO - [main.py:223] - 环境配置 - Skill ID: 
+2026-05-25 16:22:48 - mcp_services - INFO - [main.py:224] - 环境配置 - Backend Base URL: http://lzwcai-demp-corp-manager:8086
+2026-05-25 16:22:48 - mcp_services - INFO - [main.py:225] - ============================================================
+2026-05-25 16:22:48 - mcp_services - INFO - [main.py:230] - MCP 服务已启动，等待客户端连接...
+2026-05-25 16:22:51 - mcp.server.lowlevel.server - INFO - [server.py:720] - Processing request of type ListToolsRequest
+2026-05-25 16:22:51 - mcp_services - INFO - [main.py:127] - 收到列出工具请求
+2026-05-25 16:22:51 - mcp_services - INFO - [main.py:97] - 初始化查询配置，数据源: api
+2026-05-25 16:22:51 - mcp_services - INFO - [main.py:201] - 调用第三方 API，skill_id: 
+2026-05-25 16:22:51 - lzwcai_mcp_sqlexecutor.utils.api_client - INFO - [api_client.py:47] - 正在调用 API: http://lzwcai-demp-corp-manager:8086/datasource/skill/getBySkillId/
+2026-05-25 16:22:53 - lzwcai_mcp_sqlexecutor.utils.api_client - ERROR - [api_client.py:69] - API 请求异常: http://lzwcai-demp-corp-manager:8086/datasource/skill/getBySkillId/, 错误: [Errno 11001] getaddrinfo failed
+2026-05-25 16:22:53 - mcp_services - ERROR - [main.py:209] - API 调用失败: API 请求异常: http://lzwcai-demp-corp-manager:8086/datasource/skill/getBySkillId/, 错误: [Errno 11001] getaddrinfo failed
+Traceback (most recent call last):
+  File "D:\anaconda3\Lib\site-packages\httpx\_transports\default.py", line 101, in map_httpcore_exceptions
+    yield
+  File "D:\anaconda3\Lib\site-packages\httpx\_transports\default.py", line 250, in handle_request
+    resp = self._pool.handle_request(req)
+           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "D:\anaconda3\Lib\site-packages\httpcore\_sync\connection_pool.py", line 256, in handle_request
+    raise exc from None
+  File "D:\anaconda3\Lib\site-packages\httpcore\_sync\connection_pool.py", line 236, in handle_request
+    response = connection.handle_request(
+               ^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "D:\anaconda3\Lib\site-packages\httpcore\_sync\connection.py", line 101, in handle_request
+    raise exc
+  File "D:\anaconda3\Lib\site-packages\httpcore\_sync\connection.py", line 78, in handle_request
+    stream = self._connect(request)
+             ^^^^^^^^^^^^^^^^^^^^^^
+  File "D:\anaconda3\Lib\site-packages\httpcore\_sync\connection.py", line 124, in _connect
+    stream = self._network_backend.connect_tcp(**kwargs)
+             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "D:\anaconda3\Lib\site-packages\httpcore\_backends\sync.py", line 207, in connect_tcp
+    with map_exceptions(exc_map):
+  File "D:\anaconda3\Lib\contextlib.py", line 158, in __exit__
+    self.gen.throw(value)
+  File "D:\anaconda3\Lib\site-packages\httpcore\_exceptions.py", line 14, in map_exceptions
+    raise to_exc(exc) from exc
+httpcore.ConnectError: [Errno 11001] getaddrinfo failed
+
+The above exception was the direct cause of the following exception:
+
+Traceback (most recent call last):
+  File "E:\yh-ai\project\lzwcai-szyg\lzwcai-mcp-server-package\lzwcai_mcp_sqlexecutor\lzwcai_mcp_sqlexecutor\utils\api_client.py", line 50, in get_skill_by_id
+    response = self.client.get(url, headers=self._get_headers())
+               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "D:\anaconda3\Lib\site-packages\httpx\_client.py", line 1053, in get
+    return self.request(
+           ^^^^^^^^^^^^^
+  File "D:\anaconda3\Lib\site-packages\httpx\_client.py", line 825, in request
+    return self.send(request, auth=auth, follow_redirects=follow_redirects)
+           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "D:\anaconda3\Lib\site-packages\httpx\_client.py", line 914, in send
+    response = self._send_handling_auth(
+               ^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "D:\anaconda3\Lib\site-packages\httpx\_client.py", line 942, in _send_handling_auth
+    response = self._send_handling_redirects(
+               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "D:\anaconda3\Lib\site-packages\httpx\_client.py", line 979, in _send_handling_redirects
+    response = self._send_single_request(request)
+               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "D:\anaconda3\Lib\site-packages\httpx\_client.py", line 1014, in _send_single_request
+    response = transport.handle_request(request)
+               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "D:\anaconda3\Lib\site-packages\httpx\_transports\default.py", line 249, in handle_request
+    with map_httpcore_exceptions():
+  File "D:\anaconda3\Lib\contextlib.py", line 158, in __exit__
+    self.gen.throw(value)
+  File "D:\anaconda3\Lib\site-packages\httpx\_transports\default.py", line 118, in map_httpcore_exceptions
+    raise mapped_exc(message) from exc
+httpx.ConnectError: [Errno 11001] getaddrinfo failed
+
+During handling of the above exception, another exception occurred:
+
+Traceback (most recent call last):
+  File "E:\yh-ai\project\lzwcai-szyg\lzwcai-mcp-server-package\lzwcai_mcp_sqlexecutor\lzwcai_mcp_sqlexecutor\main.py", line 202, in call_third_party_api
+    raw_result = get_skill_by_id(skill_id)
+                 ^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "E:\yh-ai\project\lzwcai-szyg\lzwcai-mcp-server-package\lzwcai_mcp_sqlexecutor\lzwcai_mcp_sqlexecutor\utils\api_client.py", line 154, in get_skill_by_id
+    return default_client.get_skill_by_id(skill_id)
+           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "E:\yh-ai\project\lzwcai-szyg\lzwcai-mcp-server-package\lzwcai_mcp_sqlexecutor\lzwcai_mcp_sqlexecutor\utils\api_client.py", line 70, in get_skill_by_id
+    raise Exception(error_msg)
+Exception: API 请求异常: http://lzwcai-demp-corp-manager:8086/datasource/skill/getBySkillId/, 错误: [Errno 11001] getaddrinfo failed
+2026-05-25 16:22:53 - mcp_services - WARNING - [main.py:108] - API 获取失败，降级使用本地配置: API 请求异常: http://lzwcai-demp-corp-manager:8086/datasource/skill/getBySkillId/, 错误: [Errno 11001] getaddrinfo failed
+2026-05-25 16:22:53 - mcp_services - INFO - [main.py:58] - 成功加载 0 个业务查询配置
+2026-05-25 16:22:53 - mcp_services - INFO - [main.py:130] - 成功生成 0 个 MCP 工具
+2026-05-25 16:22:53 - mcp.server.lowlevel.server - INFO - [server.py:720] - Processing request of type ListToolsRequest
+2026-05-25 16:22:53 - mcp_services - INFO - [main.py:127] - 收到列出工具请求
+2026-05-25 16:22:53 - mcp_services - INFO - [main.py:130] - 成功生成 0 个 MCP 工具
+2026-05-25 16:23:09 - mcp.server.lowlevel.server - INFO - [server.py:720] - Processing request of type ListToolsRequest
+2026-05-25 16:23:09 - mcp_services - INFO - [main.py:127] - 收到列出工具请求
+2026-05-25 16:23:09 - mcp_services - INFO - [main.py:130] - 成功生成 0 个 MCP 工具
+2026-05-25 16:26:37 - root - INFO - [logger_config.py:151] - 日志系统初始化完成 - 日志目录: E:\yh-ai\project\lzwcai-szyg\lzwcai-mcp-server-package\lzwcai_mcp_sqlexecutor\lzwcai_mcp_sqlexecutor\logs
+2026-05-25 16:26:37 - root - INFO - [logger_config.py:152] - 日志配置 - 级别: INFO, 文件大小限制: 10MB, 备份数量: 5
+2026-05-25 16:26:37 - mcp_services - INFO - [main.py:258] - 开始运行 MCP SQL Executor 服务
+2026-05-25 16:26:37 - mcp_services - INFO - [main.py:216] - ============================================================
+2026-05-25 16:26:37 - mcp_services - INFO - [main.py:217] - 正在启动 MCP 服务: lzwcai-mcp-sqlexecutor
+2026-05-25 16:26:37 - mcp_services - INFO - [main.py:218] - 版本: 0.1.0
+2026-05-25 16:26:37 - mcp_services - INFO - [main.py:219] - ============================================================
+2026-05-25 16:26:37 - mcp_services - INFO - [main.py:222] - 环境配置 - Database ID: 240
+2026-05-25 16:26:37 - mcp_services - INFO - [main.py:223] - 环境配置 - Skill ID: 2058819964077572098
+2026-05-25 16:26:37 - mcp_services - INFO - [main.py:224] - 环境配置 - Backend Base URL: http://192.168.2.236:8088
+2026-05-25 16:26:37 - mcp_services - INFO - [main.py:225] - ============================================================
+2026-05-25 16:26:37 - mcp_services - INFO - [main.py:230] - MCP 服务已启动，等待客户端连接...
+2026-05-25 16:26:38 - mcp.server.lowlevel.server - INFO - [server.py:720] - Processing request of type ListToolsRequest
+2026-05-25 16:26:38 - mcp_services - INFO - [main.py:127] - 收到列出工具请求
+2026-05-25 16:26:38 - mcp_services - INFO - [main.py:97] - 初始化查询配置，数据源: api
+2026-05-25 16:26:38 - mcp_services - INFO - [main.py:201] - 调用第三方 API，skill_id: 2058819964077572098
+2026-05-25 16:26:38 - lzwcai_mcp_sqlexecutor.utils.api_client - INFO - [api_client.py:47] - 正在调用 API: http://192.168.2.236:8088/datasource/skill/getBySkillId/2058819964077572098
+2026-05-25 16:26:38 - httpx - INFO - [_client.py:1025] - HTTP Request: GET http://192.168.2.236:8088/datasource/skill/getBySkillId/2058819964077572098 "HTTP/1.1 200 "
+2026-05-25 16:26:38 - lzwcai_mcp_sqlexecutor.utils.api_client - INFO - [api_client.py:54] - API 调用成功: http://192.168.2.236:8088/datasource/skill/getBySkillId/2058819964077572098
+2026-05-25 16:26:38 - mcp_services - INFO - [main.py:203] - 成功获取原始响应: {'msg': '查询成功', 'code': 200, 'data': [{'id': '2058819964287287298', 'createBy': 'wxl06', 'createTime': '2026-05-25 15:58:25', 'updateBy': None, 'updateTime': None, 'serviceId': '2058819964085960705', 'uniqueName': '前50条导入数据明细查询', 'name': 'qian50tiaodaorushujumingxichaxun_32b1d628', 'description': 'qian50tiaodaorushujumingxichaxun_32b1d628: qian50tiaodaorushujumingxichaxun_32b1d628: qian50tiaodaorushujumingxichaxun_32b1d628: qian50tiaodaorushujumingxichaxun_32b1d628: 查询数据导入明细表中的前50条记录，包含原始数据、处理状态、错误原因等关键信息，用于快速预览最近的导入情况。', 'visualizable': 1, 'toolPrompt': '查询成功，返回 6 行数据，执行时间: 1ms', 'toolType': 'sql', 'datasourceId': '240', 'sqlTemplate': 'SELECT record_id AS "记录ID", task_id AS "任务ID", original_data AS "原始数据", process_result AS "处理结果", error_reason AS "错误原因", process_status AS "处理状态", target_table AS "关联目标表", created_time AS "创建时间" FROM import_record_detail LIMIT 50;', 'sqlParams': '{}', 'resultType': 'list', 'sourceType': 'ai', 'trainingTaskId': None, 'tableMetadataIds': '', 'executionCount': 0, 'visualizationConfigs': None, 'inputJsonSchema': '{"type":"object","properties":{},"required":[]}', 'outputJsonSchema': '{"type":"object","properties":{"text":{"type":"string"}},"additionalProperties":false}', 'lastExecutionTime': None}]}
+2026-05-25 16:26:38 - lzwcai_mcp_sqlexecutor.utils.api_client - INFO - [api_client.py:205] - 成功处理 1 条技能数据
+2026-05-25 16:26:38 - mcp_services - INFO - [main.py:206] - 成功处理 1 条数据
+2026-05-25 16:26:38 - mcp_services - INFO - [main.py:105] - API 配置: 1 条
+2026-05-25 16:26:38 - mcp_services - INFO - [main.py:106] - API 配置数组: [{'id': '2058819964287287298', 'businessName': 'qian50tiaodaorushujumingxichaxun_32b1d628', 'businessDescription': 'qian50tiaodaorushujumingxichaxun_32b1d628: qian50tiaodaorushujumingxichaxun_32b1d628: qian50tiaodaorushujumingxichaxun_32b1d628: qian50tiaodaorushujumingxichaxun_32b1d628: 查询数据导入明细表中的前50条记录，包含原始数据、处理状态、错误原因等关键信息，用于快速预览最近的导入情况。', 'sqlTemplate': 'SELECT record_id AS "记录ID", task_id AS "任务ID", original_data AS "原始数据", process_result AS "处理结果", error_reason AS "错误原因", process_status AS "处理状态", target_table AS "关联目标表", created_time AS "创建时间" FROM import_record_detail LIMIT 50;', 'parameters': {}, 'datasourceId': '240'}]
+2026-05-25 16:26:38 - mcp_services - INFO - [main.py:130] - 成功生成 1 个 MCP 工具

lzwcai_mcp_sqlexecutor/lzwcai_mcp_sqlexecutor/logs/lzwcai_mcp_sqlexecutor_daily.log.2026-01-26

@@ -1,223 +0,0 @@
-2025-12-31 12:57:27 - root - INFO - [logger_config.py:151] - 日志系统初始化完成 - 日志目录: E:\yh-ai\project\lzwcai-szyg\lzwcai-mcp-server-package\lzwcai_mcp_sqlexecutor\lzwcai_mcp_sqlexecutor\logs
-2025-12-31 12:57:27 - root - INFO - [logger_config.py:152] - 日志配置 - 级别: INFO, 文件大小限制: 10MB, 备份数量: 5
-2025-12-31 12:57:27 - mcp_services - INFO - [main.py:347] - 开始运行 MCP SQL Executor 服务器
-2025-12-31 12:57:27 - mcp_services - INFO - [main.py:299] - ============================================================
-2025-12-31 12:57:27 - mcp_services - INFO - [main.py:300] - 正在启动 MCP 服务器: lzwcai-mcp-sqlexecutor
-2025-12-31 12:57:27 - mcp_services - INFO - [main.py:301] - 版本: 0.1.0
-2025-12-31 12:57:27 - mcp_services - INFO - [main.py:302] - ============================================================
-2025-12-31 12:57:27 - mcp_services - INFO - [main.py:306] - 环境配置 - Database ID: 16
-2025-12-31 12:57:27 - mcp_services - INFO - [main.py:307] - 环境配置 - Skill ID: 
-2025-12-31 12:57:27 - mcp_services - INFO - [main.py:308] - 环境配置 - Backend Base URL: http://192.168.11.24:8088
-2025-12-31 12:57:27 - mcp_services - INFO - [main.py:309] - ============================================================
-2025-12-31 12:57:27 - mcp_services - INFO - [main.py:314] - MCP 服务器已启动，等待客户端连接...
-2025-12-31 12:57:28 - mcp.server.lowlevel.server - INFO - [server.py:619] - Processing request of type ListToolsRequest
-2025-12-31 12:57:28 - mcp_services - INFO - [main.py:156] - 收到列出工具请求
-2025-12-31 12:57:28 - mcp_services - INFO - [main.py:119] - 初始化查询配置（数据源: api）...
-2025-12-31 12:57:28 - mcp_services - INFO - [main.py:278] - 调用第三方API，skill_id: 
-2025-12-31 12:57:28 - lzwcai_mcp_sqlexecutor.utils.api_client - INFO - [api_client.py:71] - 正在调用API: http://192.168.11.24:8088/datasource/skill/getBySkillId/
-2025-12-31 12:57:29 - httpx - INFO - [_client.py:1025] - HTTP Request: GET http://192.168.11.24:8088/datasource/skill/getBySkillId/ "HTTP/1.1 404 "
-2025-12-31 12:57:29 - lzwcai_mcp_sqlexecutor.utils.api_client - ERROR - [api_client.py:97] - API请求失败 (HTTP 404): http://192.168.11.24:8088/datasource/skill/getBySkillId/
-2025-12-31 12:57:29 - lzwcai_mcp_sqlexecutor.utils.api_client - ERROR - [api_client.py:98] - 错误响应: {"timestamp":"2025-12-31T12:57:30.248+08:00","status":404,"error":"Not Found","path":"/datasource/skill/getBySkillId/"}
-2025-12-31 12:57:29 - mcp_services - ERROR - [main.py:292] - API调用失败: API请求失败 (HTTP 404): http://192.168.11.24:8088/datasource/skill/getBySkillId/
-Traceback (most recent call last):
-  File "E:\yh-ai\project\lzwcai-szyg\lzwcai-mcp-server-package\lzwcai_mcp_sqlexecutor\lzwcai_mcp_sqlexecutor\utils\api_client.py", line 80, in get_skill_by_id
-    response.raise_for_status()
-  File "D:\anaconda3\Lib\site-packages\httpx\_models.py", line 829, in raise_for_status
-    raise HTTPStatusError(message, request=request, response=self)
-httpx.HTTPStatusError: Client error '404 ' for url 'http://192.168.11.24:8088/datasource/skill/getBySkillId/'
-For more information check: https://developer.mozilla.org/en-US/docs/Web/HTTP/Status/404
-
-During handling of the above exception, another exception occurred:
-
-Traceback (most recent call last):
-  File "E:\yh-ai\project\lzwcai-szyg\lzwcai-mcp-server-package\lzwcai_mcp_sqlexecutor\lzwcai_mcp_sqlexecutor\main.py", line 281, in call_third_party_api
-    raw_result = get_skill_by_id(skill_id)
-                 ^^^^^^^^^^^^^^^^^^^^^^^^^
-  File "E:\yh-ai\project\lzwcai-szyg\lzwcai-mcp-server-package\lzwcai_mcp_sqlexecutor\lzwcai_mcp_sqlexecutor\utils\api_client.py", line 208, in get_skill_by_id
-    return default_client.get_skill_by_id(skill_id)
-           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-  File "E:\yh-ai\project\lzwcai-szyg\lzwcai-mcp-server-package\lzwcai_mcp_sqlexecutor\lzwcai_mcp_sqlexecutor\utils\api_client.py", line 99, in get_skill_by_id
-    raise Exception(error_msg)
-Exception: API请求失败 (HTTP 404): http://192.168.11.24:8088/datasource/skill/getBySkillId/
-2025-12-31 12:57:29 - mcp_services - WARNING - [main.py:131] - API获取失败，降级使用本地配置: API请求失败 (HTTP 404): http://192.168.11.24:8088/datasource/skill/getBySkillId/
-2025-12-31 12:57:29 - mcp_services - INFO - [main.py:55] - 成功加载 3 个业务查询配置
-2025-12-31 12:57:29 - mcp_services - ERROR - [main.py:92] - 生成工具模式失败: 2006300000000000001, 错误: 'businessName'
-Traceback (most recent call last):
-  File "E:\yh-ai\project\lzwcai-szyg\lzwcai-mcp-server-package\lzwcai_mcp_sqlexecutor\lzwcai_mcp_sqlexecutor\main.py", line 80, in generate_tool_schema_from_query
-    tool_name = query['businessName']
-                ~~~~~^^^^^^^^^^^^^^^^
-KeyError: 'businessName'
-2025-12-31 12:57:29 - mcp_services - ERROR - [main.py:170] - 列出工具失败: 'businessName'
-Traceback (most recent call last):
-  File "E:\yh-ai\project\lzwcai-szyg\lzwcai-mcp-server-package\lzwcai_mcp_sqlexecutor\lzwcai_mcp_sqlexecutor\main.py", line 162, in handle_list_tools
-    tool = generate_tool_schema_from_query(query)
-           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-  File "E:\yh-ai\project\lzwcai-szyg\lzwcai-mcp-server-package\lzwcai_mcp_sqlexecutor\lzwcai_mcp_sqlexecutor\main.py", line 80, in generate_tool_schema_from_query
-    tool_name = query['businessName']
-                ~~~~~^^^^^^^^^^^^^^^^
-KeyError: 'businessName'
-2025-12-31 12:57:29 - mcp.server.lowlevel.server - INFO - [server.py:619] - Processing request of type ListToolsRequest
-2025-12-31 12:57:29 - mcp_services - INFO - [main.py:156] - 收到列出工具请求
-2025-12-31 12:57:29 - mcp_services - ERROR - [main.py:92] - 生成工具模式失败: 2006300000000000001, 错误: 'businessName'
-Traceback (most recent call last):
-  File "E:\yh-ai\project\lzwcai-szyg\lzwcai-mcp-server-package\lzwcai_mcp_sqlexecutor\lzwcai_mcp_sqlexecutor\main.py", line 80, in generate_tool_schema_from_query
-    tool_name = query['businessName']
-                ~~~~~^^^^^^^^^^^^^^^^
-KeyError: 'businessName'
-2025-12-31 12:57:29 - mcp_services - ERROR - [main.py:170] - 列出工具失败: 'businessName'
-Traceback (most recent call last):
-  File "E:\yh-ai\project\lzwcai-szyg\lzwcai-mcp-server-package\lzwcai_mcp_sqlexecutor\lzwcai_mcp_sqlexecutor\main.py", line 162, in handle_list_tools
-    tool = generate_tool_schema_from_query(query)
-           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-  File "E:\yh-ai\project\lzwcai-szyg\lzwcai-mcp-server-package\lzwcai_mcp_sqlexecutor\lzwcai_mcp_sqlexecutor\main.py", line 80, in generate_tool_schema_from_query
-    tool_name = query['businessName']
-                ~~~~~^^^^^^^^^^^^^^^^
-KeyError: 'businessName'
-2025-12-31 12:57:54 - root - INFO - [logger_config.py:151] - 日志系统初始化完成 - 日志目录: E:\yh-ai\project\lzwcai-szyg\lzwcai-mcp-server-package\lzwcai_mcp_sqlexecutor\lzwcai_mcp_sqlexecutor\logs
-2025-12-31 12:57:54 - root - INFO - [logger_config.py:152] - 日志配置 - 级别: INFO, 文件大小限制: 10MB, 备份数量: 5
-2025-12-31 12:57:54 - mcp_services - INFO - [main.py:347] - 开始运行 MCP SQL Executor 服务器
-2025-12-31 12:57:54 - mcp_services - INFO - [main.py:299] - ============================================================
-2025-12-31 12:57:54 - mcp_services - INFO - [main.py:300] - 正在启动 MCP 服务器: lzwcai-mcp-sqlexecutor
-2025-12-31 12:57:54 - mcp_services - INFO - [main.py:301] - 版本: 0.1.0
-2025-12-31 12:57:54 - mcp_services - INFO - [main.py:302] - ============================================================
-2025-12-31 12:57:54 - mcp_services - INFO - [main.py:306] - 环境配置 - Database ID: 16
-2025-12-31 12:57:54 - mcp_services - INFO - [main.py:307] - 环境配置 - Skill ID: 
-2025-12-31 12:57:54 - mcp_services - INFO - [main.py:308] - 环境配置 - Backend Base URL: http://192.168.11.24:8088
-2025-12-31 12:57:54 - mcp_services - INFO - [main.py:309] - ============================================================
-2025-12-31 12:57:54 - mcp_services - INFO - [main.py:314] - MCP 服务器已启动，等待客户端连接...
-2025-12-31 12:57:54 - mcp.server.lowlevel.server - INFO - [server.py:619] - Processing request of type ListToolsRequest
-2025-12-31 12:57:54 - mcp_services - INFO - [main.py:156] - 收到列出工具请求
-2025-12-31 12:57:54 - mcp_services - INFO - [main.py:119] - 初始化查询配置（数据源: local）...
-2025-12-31 12:57:54 - mcp_services - INFO - [main.py:55] - 成功加载 3 个业务查询配置
-2025-12-31 12:57:54 - mcp_services - INFO - [main.py:123] - 本地配置: 3 条
-2025-12-31 12:57:54 - mcp_services - ERROR - [main.py:92] - 生成工具模式失败: 2006300000000000001, 错误: 'businessName'
-Traceback (most recent call last):
-  File "E:\yh-ai\project\lzwcai-szyg\lzwcai-mcp-server-package\lzwcai_mcp_sqlexecutor\lzwcai_mcp_sqlexecutor\main.py", line 80, in generate_tool_schema_from_query
-    tool_name = query['businessName']
-                ~~~~~^^^^^^^^^^^^^^^^
-KeyError: 'businessName'
-2025-12-31 12:57:54 - mcp_services - ERROR - [main.py:170] - 列出工具失败: 'businessName'
-Traceback (most recent call last):
-  File "E:\yh-ai\project\lzwcai-szyg\lzwcai-mcp-server-package\lzwcai_mcp_sqlexecutor\lzwcai_mcp_sqlexecutor\main.py", line 162, in handle_list_tools
-    tool = generate_tool_schema_from_query(query)
-           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-  File "E:\yh-ai\project\lzwcai-szyg\lzwcai-mcp-server-package\lzwcai_mcp_sqlexecutor\lzwcai_mcp_sqlexecutor\main.py", line 80, in generate_tool_schema_from_query
-    tool_name = query['businessName']
-                ~~~~~^^^^^^^^^^^^^^^^
-KeyError: 'businessName'
-2025-12-31 15:00:31 - mcp.server.lowlevel.server - INFO - [server.py:619] - Processing request of type ListToolsRequest
-2025-12-31 15:00:31 - mcp_services - INFO - [main.py:156] - 收到列出工具请求
-2025-12-31 15:00:31 - mcp_services - ERROR - [main.py:92] - 生成工具模式失败: 2006300000000000001, 错误: 'businessName'
-Traceback (most recent call last):
-  File "E:\yh-ai\project\lzwcai-szyg\lzwcai-mcp-server-package\lzwcai_mcp_sqlexecutor\lzwcai_mcp_sqlexecutor\main.py", line 80, in generate_tool_schema_from_query
-    tool_name = query['businessName']
-                ~~~~~^^^^^^^^^^^^^^^^
-KeyError: 'businessName'
-2025-12-31 15:00:31 - mcp_services - ERROR - [main.py:170] - 列出工具失败: 'businessName'
-Traceback (most recent call last):
-  File "E:\yh-ai\project\lzwcai-szyg\lzwcai-mcp-server-package\lzwcai_mcp_sqlexecutor\lzwcai_mcp_sqlexecutor\main.py", line 162, in handle_list_tools
-    tool = generate_tool_schema_from_query(query)
-           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-  File "E:\yh-ai\project\lzwcai-szyg\lzwcai-mcp-server-package\lzwcai_mcp_sqlexecutor\lzwcai_mcp_sqlexecutor\main.py", line 80, in generate_tool_schema_from_query
-    tool_name = query['businessName']
-                ~~~~~^^^^^^^^^^^^^^^^
-KeyError: 'businessName'
-2025-12-31 15:00:34 - mcp_services - INFO - [main.py:329] - MCP 服务器已关闭
-2025-12-31 15:00:53 - root - INFO - [logger_config.py:151] - 日志系统初始化完成 - 日志目录: E:\yh-ai\project\lzwcai-szyg\lzwcai-mcp-server-package\lzwcai_mcp_sqlexecutor\lzwcai_mcp_sqlexecutor\logs
-2025-12-31 15:00:53 - root - INFO - [logger_config.py:152] - 日志配置 - 级别: INFO, 文件大小限制: 10MB, 备份数量: 5
-2025-12-31 15:00:53 - mcp_services - INFO - [main.py:347] - 开始运行 MCP SQL Executor 服务器
-2025-12-31 15:00:53 - mcp_services - INFO - [main.py:299] - ============================================================
-2025-12-31 15:00:53 - mcp_services - INFO - [main.py:300] - 正在启动 MCP 服务器: lzwcai-mcp-sqlexecutor
-2025-12-31 15:00:53 - mcp_services - INFO - [main.py:301] - 版本: 0.1.0
-2025-12-31 15:00:53 - mcp_services - INFO - [main.py:302] - ============================================================
-2025-12-31 15:00:53 - mcp_services - INFO - [main.py:306] - 环境配置 - Database ID: 29
-2025-12-31 15:00:53 - mcp_services - INFO - [main.py:307] - 环境配置 - Skill ID: 
-2025-12-31 15:00:53 - mcp_services - INFO - [main.py:308] - 环境配置 - Backend Base URL: http://lzwcai-demp-corp-manager:8086
-2025-12-31 15:00:53 - mcp_services - INFO - [main.py:309] - ============================================================
-2025-12-31 15:00:53 - mcp_services - INFO - [main.py:314] - MCP 服务器已启动，等待客户端连接...
-2025-12-31 15:00:54 - mcp.server.lowlevel.server - INFO - [server.py:619] - Processing request of type ListToolsRequest
-2025-12-31 15:00:54 - mcp_services - INFO - [main.py:156] - 收到列出工具请求
-2025-12-31 15:00:54 - mcp_services - INFO - [main.py:119] - 初始化查询配置（数据源: api）...
-2025-12-31 15:00:54 - mcp_services - INFO - [main.py:278] - 调用第三方API，skill_id: 
-2025-12-31 15:00:54 - lzwcai_mcp_sqlexecutor.utils.api_client - INFO - [api_client.py:71] - 正在调用API: http://lzwcai-demp-corp-manager:8086/datasource/skill/getBySkillId/
-2025-12-31 15:00:56 - lzwcai_mcp_sqlexecutor.utils.api_client - ERROR - [api_client.py:103] - API请求异常: http://lzwcai-demp-corp-manager:8086/datasource/skill/getBySkillId/, 错误: [Errno 11001] getaddrinfo failed
-2025-12-31 15:00:56 - mcp_services - ERROR - [main.py:292] - API调用失败: API请求异常: http://lzwcai-demp-corp-manager:8086/datasource/skill/getBySkillId/, 错误: [Errno 11001] getaddrinfo failed
-Traceback (most recent call last):
-  File "D:\anaconda3\Lib\site-packages\httpx\_transports\default.py", line 101, in map_httpcore_exceptions
-    yield
-  File "D:\anaconda3\Lib\site-packages\httpx\_transports\default.py", line 250, in handle_request
-    resp = self._pool.handle_request(req)
-           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-  File "D:\anaconda3\Lib\site-packages\httpcore\_sync\connection_pool.py", line 216, in handle_request
-    raise exc from None
-  File "D:\anaconda3\Lib\site-packages\httpcore\_sync\connection_pool.py", line 196, in handle_request
-    response = connection.handle_request(
-               ^^^^^^^^^^^^^^^^^^^^^^^^^^
-  File "D:\anaconda3\Lib\site-packages\httpcore\_sync\connection.py", line 99, in handle_request
-    raise exc
-  File "D:\anaconda3\Lib\site-packages\httpcore\_sync\connection.py", line 76, in handle_request
-    stream = self._connect(request)
-             ^^^^^^^^^^^^^^^^^^^^^^
-  File "D:\anaconda3\Lib\site-packages\httpcore\_sync\connection.py", line 122, in _connect
-    stream = self._network_backend.connect_tcp(**kwargs)
-             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-  File "D:\anaconda3\Lib\site-packages\httpcore\_backends\sync.py", line 205, in connect_tcp
-    with map_exceptions(exc_map):
-         ^^^^^^^^^^^^^^^^^^^^^^^
-  File "D:\anaconda3\Lib\contextlib.py", line 158, in __exit__
-    self.gen.throw(value)
-  File "D:\anaconda3\Lib\site-packages\httpcore\_exceptions.py", line 14, in map_exceptions
-    raise to_exc(exc) from exc
-httpcore.ConnectError: [Errno 11001] getaddrinfo failed
-
-The above exception was the direct cause of the following exception:
-
-Traceback (most recent call last):
-  File "E:\yh-ai\project\lzwcai-szyg\lzwcai-mcp-server-package\lzwcai_mcp_sqlexecutor\lzwcai_mcp_sqlexecutor\utils\api_client.py", line 74, in get_skill_by_id
-    response = self.client.get(
-               ^^^^^^^^^^^^^^^^
-  File "D:\anaconda3\Lib\site-packages\httpx\_client.py", line 1053, in get
-    return self.request(
-           ^^^^^^^^^^^^^
-  File "D:\anaconda3\Lib\site-packages\httpx\_client.py", line 825, in request
-    return self.send(request, auth=auth, follow_redirects=follow_redirects)
-           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-  File "D:\anaconda3\Lib\site-packages\httpx\_client.py", line 914, in send
-    response = self._send_handling_auth(
-               ^^^^^^^^^^^^^^^^^^^^^^^^^
-  File "D:\anaconda3\Lib\site-packages\httpx\_client.py", line 942, in _send_handling_auth
-    response = self._send_handling_redirects(
-               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-  File "D:\anaconda3\Lib\site-packages\httpx\_client.py", line 979, in _send_handling_redirects
-    response = self._send_single_request(request)
-               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-  File "D:\anaconda3\Lib\site-packages\httpx\_client.py", line 1014, in _send_single_request
-    response = transport.handle_request(request)
-               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-  File "D:\anaconda3\Lib\site-packages\httpx\_transports\default.py", line 249, in handle_request
-    with map_httpcore_exceptions():
-         ^^^^^^^^^^^^^^^^^^^^^^^^^
-  File "D:\anaconda3\Lib\contextlib.py", line 158, in __exit__
-    self.gen.throw(value)
-  File "D:\anaconda3\Lib\site-packages\httpx\_transports\default.py", line 118, in map_httpcore_exceptions
-    raise mapped_exc(message) from exc
-httpx.ConnectError: [Errno 11001] getaddrinfo failed
-
-During handling of the above exception, another exception occurred:
-
-Traceback (most recent call last):
-  File "E:\yh-ai\project\lzwcai-szyg\lzwcai-mcp-server-package\lzwcai_mcp_sqlexecutor\lzwcai_mcp_sqlexecutor\main.py", line 281, in call_third_party_api
-    raw_result = get_skill_by_id(skill_id)
-                 ^^^^^^^^^^^^^^^^^^^^^^^^^
-  File "E:\yh-ai\project\lzwcai-szyg\lzwcai-mcp-server-package\lzwcai_mcp_sqlexecutor\lzwcai_mcp_sqlexecutor\utils\api_client.py", line 208, in get_skill_by_id
-    return default_client.get_skill_by_id(skill_id)
-           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-  File "E:\yh-ai\project\lzwcai-szyg\lzwcai-mcp-server-package\lzwcai_mcp_sqlexecutor\lzwcai_mcp_sqlexecutor\utils\api_client.py", line 104, in get_skill_by_id
-    raise Exception(error_msg)
-Exception: API请求异常: http://lzwcai-demp-corp-manager:8086/datasource/skill/getBySkillId/, 错误: [Errno 11001] getaddrinfo failed
-2025-12-31 15:00:56 - mcp_services - WARNING - [main.py:131] - API获取失败，降级使用本地配置: API请求异常: http://lzwcai-demp-corp-manager:8086/datasource/skill/getBySkillId/, 错误: [Errno 11001] getaddrinfo failed
-2025-12-31 15:00:56 - mcp_services - INFO - [main.py:55] - 成功加载 0 个业务查询配置
-2025-12-31 15:00:56 - mcp_services - INFO - [main.py:165] - 成功生成 0 个 MCP 工具
-2025-12-31 15:00:56 - mcp.server.lowlevel.server - INFO - [server.py:619] - Processing request of type ListToolsRequest
-2025-12-31 15:00:56 - mcp_services - INFO - [main.py:156] - 收到列出工具请求
-2025-12-31 15:00:56 - mcp_services - INFO - [main.py:165] - 成功生成 0 个 MCP 工具

lzwcai_mcp_sqlexecutor/lzwcai_mcp_sqlexecutor/logs/lzwcai_mcp_sqlexecutor_error.log

@@ -1,110 +1,26 @@
-2025-12-31 12:57:29 - lzwcai_mcp_sqlexecutor.utils.api_client - ERROR - [api_client.py:97] - API请求失败 (HTTP 404): http://192.168.11.24:8088/datasource/skill/getBySkillId/
+2026-05-25 16:22:53 - lzwcai_mcp_sqlexecutor.utils.api_client - ERROR - [api_client.py:69] - API 请求异常: http://lzwcai-demp-corp-manager:8086/datasource/skill/getBySkillId/, 错误: [Errno 11001] getaddrinfo failed
-2025-12-31 12:57:29 - lzwcai_mcp_sqlexecutor.utils.api_client - ERROR - [api_client.py:98] - 错误响应: {"timestamp":"2025-12-31T12:57:30.248+08:00","status":404,"error":"Not Found","path":"/datasource/skill/getBySkillId/"}
+2026-05-25 16:22:53 - mcp_services - ERROR - [main.py:209] - API 调用失败: API 请求异常: http://lzwcai-demp-corp-manager:8086/datasource/skill/getBySkillId/, 错误: [Errno 11001] getaddrinfo failed
-2025-12-31 12:57:29 - mcp_services - ERROR - [main.py:292] - API调用失败: API请求失败 (HTTP 404): http://192.168.11.24:8088/datasource/skill/getBySkillId/
-Traceback (most recent call last):
-  File "E:\yh-ai\project\lzwcai-szyg\lzwcai-mcp-server-package\lzwcai_mcp_sqlexecutor\lzwcai_mcp_sqlexecutor\utils\api_client.py", line 80, in get_skill_by_id
-    response.raise_for_status()
-  File "D:\anaconda3\Lib\site-packages\httpx\_models.py", line 829, in raise_for_status
-    raise HTTPStatusError(message, request=request, response=self)
-httpx.HTTPStatusError: Client error '404 ' for url 'http://192.168.11.24:8088/datasource/skill/getBySkillId/'
-For more information check: https://developer.mozilla.org/en-US/docs/Web/HTTP/Status/404
-
-During handling of the above exception, another exception occurred:
-
-Traceback (most recent call last):
-  File "E:\yh-ai\project\lzwcai-szyg\lzwcai-mcp-server-package\lzwcai_mcp_sqlexecutor\lzwcai_mcp_sqlexecutor\main.py", line 281, in call_third_party_api
-    raw_result = get_skill_by_id(skill_id)
-                 ^^^^^^^^^^^^^^^^^^^^^^^^^
-  File "E:\yh-ai\project\lzwcai-szyg\lzwcai-mcp-server-package\lzwcai_mcp_sqlexecutor\lzwcai_mcp_sqlexecutor\utils\api_client.py", line 208, in get_skill_by_id
-    return default_client.get_skill_by_id(skill_id)
-           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-  File "E:\yh-ai\project\lzwcai-szyg\lzwcai-mcp-server-package\lzwcai_mcp_sqlexecutor\lzwcai_mcp_sqlexecutor\utils\api_client.py", line 99, in get_skill_by_id
-    raise Exception(error_msg)
-Exception: API请求失败 (HTTP 404): http://192.168.11.24:8088/datasource/skill/getBySkillId/
-2025-12-31 12:57:29 - mcp_services - ERROR - [main.py:92] - 生成工具模式失败: 2006300000000000001, 错误: 'businessName'
-Traceback (most recent call last):
-  File "E:\yh-ai\project\lzwcai-szyg\lzwcai-mcp-server-package\lzwcai_mcp_sqlexecutor\lzwcai_mcp_sqlexecutor\main.py", line 80, in generate_tool_schema_from_query
-    tool_name = query['businessName']
-                ~~~~~^^^^^^^^^^^^^^^^
-KeyError: 'businessName'
-2025-12-31 12:57:29 - mcp_services - ERROR - [main.py:170] - 列出工具失败: 'businessName'
-Traceback (most recent call last):
-  File "E:\yh-ai\project\lzwcai-szyg\lzwcai-mcp-server-package\lzwcai_mcp_sqlexecutor\lzwcai_mcp_sqlexecutor\main.py", line 162, in handle_list_tools
-    tool = generate_tool_schema_from_query(query)
-           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-  File "E:\yh-ai\project\lzwcai-szyg\lzwcai-mcp-server-package\lzwcai_mcp_sqlexecutor\lzwcai_mcp_sqlexecutor\main.py", line 80, in generate_tool_schema_from_query
-    tool_name = query['businessName']
-                ~~~~~^^^^^^^^^^^^^^^^
-KeyError: 'businessName'
-2025-12-31 12:57:29 - mcp_services - ERROR - [main.py:92] - 生成工具模式失败: 2006300000000000001, 错误: 'businessName'
-Traceback (most recent call last):
-  File "E:\yh-ai\project\lzwcai-szyg\lzwcai-mcp-server-package\lzwcai_mcp_sqlexecutor\lzwcai_mcp_sqlexecutor\main.py", line 80, in generate_tool_schema_from_query
-    tool_name = query['businessName']
-                ~~~~~^^^^^^^^^^^^^^^^
-KeyError: 'businessName'
-2025-12-31 12:57:29 - mcp_services - ERROR - [main.py:170] - 列出工具失败: 'businessName'
-Traceback (most recent call last):
-  File "E:\yh-ai\project\lzwcai-szyg\lzwcai-mcp-server-package\lzwcai_mcp_sqlexecutor\lzwcai_mcp_sqlexecutor\main.py", line 162, in handle_list_tools
-    tool = generate_tool_schema_from_query(query)
-           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-  File "E:\yh-ai\project\lzwcai-szyg\lzwcai-mcp-server-package\lzwcai_mcp_sqlexecutor\lzwcai_mcp_sqlexecutor\main.py", line 80, in generate_tool_schema_from_query
-    tool_name = query['businessName']
-                ~~~~~^^^^^^^^^^^^^^^^
-KeyError: 'businessName'
-2025-12-31 12:57:54 - mcp_services - ERROR - [main.py:92] - 生成工具模式失败: 2006300000000000001, 错误: 'businessName'
-Traceback (most recent call last):
-  File "E:\yh-ai\project\lzwcai-szyg\lzwcai-mcp-server-package\lzwcai_mcp_sqlexecutor\lzwcai_mcp_sqlexecutor\main.py", line 80, in generate_tool_schema_from_query
-    tool_name = query['businessName']
-                ~~~~~^^^^^^^^^^^^^^^^
-KeyError: 'businessName'
-2025-12-31 12:57:54 - mcp_services - ERROR - [main.py:170] - 列出工具失败: 'businessName'
-Traceback (most recent call last):
-  File "E:\yh-ai\project\lzwcai-szyg\lzwcai-mcp-server-package\lzwcai_mcp_sqlexecutor\lzwcai_mcp_sqlexecutor\main.py", line 162, in handle_list_tools
-    tool = generate_tool_schema_from_query(query)
-           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-  File "E:\yh-ai\project\lzwcai-szyg\lzwcai-mcp-server-package\lzwcai_mcp_sqlexecutor\lzwcai_mcp_sqlexecutor\main.py", line 80, in generate_tool_schema_from_query
-    tool_name = query['businessName']
-                ~~~~~^^^^^^^^^^^^^^^^
-KeyError: 'businessName'
-2025-12-31 15:00:31 - mcp_services - ERROR - [main.py:92] - 生成工具模式失败: 2006300000000000001, 错误: 'businessName'
-Traceback (most recent call last):
-  File "E:\yh-ai\project\lzwcai-szyg\lzwcai-mcp-server-package\lzwcai_mcp_sqlexecutor\lzwcai_mcp_sqlexecutor\main.py", line 80, in generate_tool_schema_from_query
-    tool_name = query['businessName']
-                ~~~~~^^^^^^^^^^^^^^^^
-KeyError: 'businessName'
-2025-12-31 15:00:31 - mcp_services - ERROR - [main.py:170] - 列出工具失败: 'businessName'
-Traceback (most recent call last):
-  File "E:\yh-ai\project\lzwcai-szyg\lzwcai-mcp-server-package\lzwcai_mcp_sqlexecutor\lzwcai_mcp_sqlexecutor\main.py", line 162, in handle_list_tools
-    tool = generate_tool_schema_from_query(query)
-           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-  File "E:\yh-ai\project\lzwcai-szyg\lzwcai-mcp-server-package\lzwcai_mcp_sqlexecutor\lzwcai_mcp_sqlexecutor\main.py", line 80, in generate_tool_schema_from_query
-    tool_name = query['businessName']
-                ~~~~~^^^^^^^^^^^^^^^^
-KeyError: 'businessName'
-2025-12-31 15:00:56 - lzwcai_mcp_sqlexecutor.utils.api_client - ERROR - [api_client.py:103] - API请求异常: http://lzwcai-demp-corp-manager:8086/datasource/skill/getBySkillId/, 错误: [Errno 11001] getaddrinfo failed
-2025-12-31 15:00:56 - mcp_services - ERROR - [main.py:292] - API调用失败: API请求异常: http://lzwcai-demp-corp-manager:8086/datasource/skill/getBySkillId/, 错误: [Errno 11001] getaddrinfo failed
 Traceback (most recent call last):
   File "D:\anaconda3\Lib\site-packages\httpx\_transports\default.py", line 101, in map_httpcore_exceptions
     yield
   File "D:\anaconda3\Lib\site-packages\httpx\_transports\default.py", line 250, in handle_request
     resp = self._pool.handle_request(req)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-  File "D:\anaconda3\Lib\site-packages\httpcore\_sync\connection_pool.py", line 216, in handle_request
+  File "D:\anaconda3\Lib\site-packages\httpcore\_sync\connection_pool.py", line 256, in handle_request
     raise exc from None
-  File "D:\anaconda3\Lib\site-packages\httpcore\_sync\connection_pool.py", line 196, in handle_request
+  File "D:\anaconda3\Lib\site-packages\httpcore\_sync\connection_pool.py", line 236, in handle_request
     response = connection.handle_request(
                ^^^^^^^^^^^^^^^^^^^^^^^^^^
-  File "D:\anaconda3\Lib\site-packages\httpcore\_sync\connection.py", line 99, in handle_request
+  File "D:\anaconda3\Lib\site-packages\httpcore\_sync\connection.py", line 101, in handle_request
     raise exc
-  File "D:\anaconda3\Lib\site-packages\httpcore\_sync\connection.py", line 76, in handle_request
+  File "D:\anaconda3\Lib\site-packages\httpcore\_sync\connection.py", line 78, in handle_request
     stream = self._connect(request)
              ^^^^^^^^^^^^^^^^^^^^^^
-  File "D:\anaconda3\Lib\site-packages\httpcore\_sync\connection.py", line 122, in _connect
+  File "D:\anaconda3\Lib\site-packages\httpcore\_sync\connection.py", line 124, in _connect
     stream = self._network_backend.connect_tcp(**kwargs)
              ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-  File "D:\anaconda3\Lib\site-packages\httpcore\_backends\sync.py", line 205, in connect_tcp
+  File "D:\anaconda3\Lib\site-packages\httpcore\_backends\sync.py", line 207, in connect_tcp
     with map_exceptions(exc_map):
-         ^^^^^^^^^^^^^^^^^^^^^^^
   File "D:\anaconda3\Lib\contextlib.py", line 158, in __exit__
     self.gen.throw(value)
   File "D:\anaconda3\Lib\site-packages\httpcore\_exceptions.py", line 14, in map_exceptions
@@ -114,9 +30,9 @@ httpcore.ConnectError: [Errno 11001] getaddrinfo failed
 The above exception was the direct cause of the following exception:
 
 Traceback (most recent call last):
-  File "E:\yh-ai\project\lzwcai-szyg\lzwcai-mcp-server-package\lzwcai_mcp_sqlexecutor\lzwcai_mcp_sqlexecutor\utils\api_client.py", line 74, in get_skill_by_id
+  File "E:\yh-ai\project\lzwcai-szyg\lzwcai-mcp-server-package\lzwcai_mcp_sqlexecutor\lzwcai_mcp_sqlexecutor\utils\api_client.py", line 50, in get_skill_by_id
-    response = self.client.get(
+    response = self.client.get(url, headers=self._get_headers())
-               ^^^^^^^^^^^^^^^^
+               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
   File "D:\anaconda3\Lib\site-packages\httpx\_client.py", line 1053, in get
     return self.request(
            ^^^^^^^^^^^^^
@@ -137,7 +53,6 @@ Traceback (most recent call last):
                ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
   File "D:\anaconda3\Lib\site-packages\httpx\_transports\default.py", line 249, in handle_request
     with map_httpcore_exceptions():
-         ^^^^^^^^^^^^^^^^^^^^^^^^^
   File "D:\anaconda3\Lib\contextlib.py", line 158, in __exit__
     self.gen.throw(value)
   File "D:\anaconda3\Lib\site-packages\httpx\_transports\default.py", line 118, in map_httpcore_exceptions
@@ -147,12 +62,12 @@ httpx.ConnectError: [Errno 11001] getaddrinfo failed
 During handling of the above exception, another exception occurred:
 
 Traceback (most recent call last):
-  File "E:\yh-ai\project\lzwcai-szyg\lzwcai-mcp-server-package\lzwcai_mcp_sqlexecutor\lzwcai_mcp_sqlexecutor\main.py", line 281, in call_third_party_api
+  File "E:\yh-ai\project\lzwcai-szyg\lzwcai-mcp-server-package\lzwcai_mcp_sqlexecutor\lzwcai_mcp_sqlexecutor\main.py", line 202, in call_third_party_api
     raw_result = get_skill_by_id(skill_id)
                  ^^^^^^^^^^^^^^^^^^^^^^^^^
-  File "E:\yh-ai\project\lzwcai-szyg\lzwcai-mcp-server-package\lzwcai_mcp_sqlexecutor\lzwcai_mcp_sqlexecutor\utils\api_client.py", line 208, in get_skill_by_id
+  File "E:\yh-ai\project\lzwcai-szyg\lzwcai-mcp-server-package\lzwcai_mcp_sqlexecutor\lzwcai_mcp_sqlexecutor\utils\api_client.py", line 154, in get_skill_by_id
     return default_client.get_skill_by_id(skill_id)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-  File "E:\yh-ai\project\lzwcai-szyg\lzwcai-mcp-server-package\lzwcai_mcp_sqlexecutor\lzwcai_mcp_sqlexecutor\utils\api_client.py", line 104, in get_skill_by_id
+  File "E:\yh-ai\project\lzwcai-szyg\lzwcai-mcp-server-package\lzwcai_mcp_sqlexecutor\lzwcai_mcp_sqlexecutor\utils\api_client.py", line 70, in get_skill_by_id
     raise Exception(error_msg)
-Exception: API请求异常: http://lzwcai-demp-corp-manager:8086/datasource/skill/getBySkillId/, 错误: [Errno 11001] getaddrinfo failed
+Exception: API 请求异常: http://lzwcai-demp-corp-manager:8086/datasource/skill/getBySkillId/, 错误: [Errno 11001] getaddrinfo failed

lzwcai_mcp_sqlexecutor/lzwcai_mcp_sqlexecutor/main.py

@@ -1,13 +1,13 @@
 from pathlib import Path
 from typing import Any
 import asyncio
+import json
 import logging
 
-# 支持直接运行和模块导入两种方式
 try:
-    from .utils import load_json, generate_tool_name, generate_input_schema
+    from .utils import load_json, generate_input_schema
-    from .utils import get_skill_by_id, DataSourceAPIClient, process_skill_response, test_sql_with_schema
+    from .utils import get_skill_by_id, process_skill_response, test_sql_with_schema
-    from .utils import get_database_id, get_skill_id, get_env_config
+    from .utils import get_skill_id, get_env_config
     from .utils.logger_config import logger_config
 except ImportError:
     from utils import load_json, generate_input_schema
@@ -19,41 +19,43 @@ from mcp.server.models import InitializationOptions
 from mcp.server import NotificationOptions, Server
 import mcp.types as types
 
-# 初始化 MCP 专用日志器
+
 mcp_logger = logger_config.setup_mcp_logging()
 
-# ========== 数据源配置 ==========
+DATA_SOURCE_API = "api"
-# 数据源类型常量
+DATA_SOURCE_LOCAL = "local"
-DATA_SOURCE_API = "api"      # 仅使用API数据
+DATA_SOURCE_BOTH = "both"
-DATA_SOURCE_LOCAL = "local"  # 仅使用本地JSON数据
-DATA_SOURCE_BOTH = "both"    # 合并本地和API数据
-
-# 默认数据源（可修改）
 DEFAULT_DATA_SOURCE = DATA_SOURCE_API
-# ================================
+
+
+def _text_response(payload: dict[str, Any]) -> list[types.TextContent]:
+    """Build a JSON text response."""
+    return [
+        types.TextContent(
+            type="text",
+            text=json.dumps(payload, ensure_ascii=False, indent=2)
+        )
+    ]
+
+
+def _extract_user_id(arguments: dict[str, Any]) -> Any:
+    """Allow numeric 0, reject None and blank strings."""
+    user_id = arguments.get("userId")
+    if user_id is None:
+        return None
+    if isinstance(user_id, str) and not user_id.strip():
+        return None
+    return user_id
 
 
 def get_queries():
-    """
+    """Read local business query config."""
-    获取业务查询配置
-    
-    Returns:
-        list: 包含所有业务查询配置的列表
-    """
     try:
-        # 获取当前文件所在目录
         current_dir = Path(__file__).parent
-        
-        # 构建 businessQueries.json 的路径
         json_path = current_dir / "businessQueries.json"
-        
         mcp_logger.debug(f"正在读取业务查询配置文件: {json_path}")
-        
-        # 使用 load_json 方法读取 JSON 文件
         queries = load_json(json_path)
-        
         mcp_logger.info(f"成功加载 {len(queries)} 个业务查询配置")
-        
         return queries
     except Exception as e:
         mcp_logger.error(f"加载业务查询配置失败: {e}", exc_info=True)
@@ -61,110 +63,72 @@ def get_queries():
 
 
 def generate_tool_schema_from_query(query: dict) -> types.Tool:
-    """
+    """Generate an MCP tool definition from one query config."""
-    根据查询配置生成 MCP 工具模式
-    
-    Args:
-        query: 单个查询配置字典
-        
-    Returns:
-        types.Tool: MCP 工具对象
-    """
     try:
-        # 获取参数定义并生成 inputSchema
+        parameters = query.get("parameters", {})
-        parameters = query.get('parameters', {})
         input_schema = generate_input_schema(parameters)
-        
+        tool_name = query["businessName"]
-        # 生成工具名称（格式: tool_拼音_id）
-        # tool_name = generate_tool_name(query['businessName'], query['id'])
-        tool_name = query['businessName']
-        # 构建工具描述，包含业务名称和业务描述
         description = f"{query['businessName']}: {query['businessDescription']}"
-        
+
         mcp_logger.debug(f"生成工具模式: {tool_name} - {query['businessName']}")
-        
+
         return types.Tool(
             name=tool_name,
             description=description,
             inputSchema=input_schema
         )
     except Exception as e:
-        mcp_logger.error(f"生成工具模式失败: {query.get('id', 'unknown')}, 错误: {e}", exc_info=True)
+        mcp_logger.error(
+            f"生成工具模式失败: {query.get('id', 'unknown')}, 错误: {e}",
+            exc_info=True
+        )
         raise
 
 
-# 创建 MCP 服务器实例
 server = Server("lzwcai-mcp-sqlexecutor")
-
-# 缓存查询配置，避免重复加载
 _queries_cache = None
 
 
 async def get_queries_cache(source: str = None):
-    """
+    """Get or initialize query config cache."""
-    获取或初始化查询配置缓存
-    
-    Args:
-        source: 数据源类型（默认使用 DEFAULT_DATA_SOURCE）
-            - "api": 仅使用API数据
-            - "local": 仅使用本地JSON数据
-            - "both": 合并本地和API数据
-    
-    Returns:
-        查询配置列表
-    """
     global _queries_cache
     if _queries_cache is None:
         source = source or DEFAULT_DATA_SOURCE
-        mcp_logger.info(f"初始化查询配置（数据源: {source}）...")
+        mcp_logger.info(f"初始化查询配置，数据源: {source}")
-        
+
         if source == DATA_SOURCE_LOCAL:
             _queries_cache = get_queries()
             mcp_logger.info(f"本地配置: {len(_queries_cache)} 条")
-            
         elif source == DATA_SOURCE_API:
             try:
                 _queries_cache = await call_third_party_api()
-                mcp_logger.info(f"API配置: {len(_queries_cache)} 条")
+                mcp_logger.info(f"API 配置: {len(_queries_cache)} 条")
-                mcp_logger.info(f"API配置数组: {_queries_cache}")
+                mcp_logger.info(f"API 配置数组: {_queries_cache}")
             except Exception as e:
-                mcp_logger.warning(f"API获取失败，降级使用本地配置: {e}")
+                mcp_logger.warning(f"API 获取失败，降级使用本地配置: {e}")
                 _queries_cache = get_queries()
-                
+        else:
-        else:  # DATA_SOURCE_BOTH
             local = get_queries()
             try:
                 api = await call_third_party_api()
             except Exception as e:
-                mcp_logger.warning(f"API获取失败: {e}")
+                mcp_logger.warning(f"API 获取失败: {e}")
                 api = []
             _queries_cache = local + api
-            mcp_logger.info(f"配置总数: {len(_queries_cache)} 条（本地{len(local)}+API{len(api)}）")
+            mcp_logger.info(f"配置总数: {len(_queries_cache)} 条，本地 {len(local)} + API {len(api)}")
-        
+
     return _queries_cache
 
 
 @server.list_tools()
 async def handle_list_tools() -> list[types.Tool]:
-    """
+    """List all dynamically generated MCP tools."""
-    列出所有动态生成的 MCP 工具
-    
-    Returns:
-        list[types.Tool]: 所有可用的工具列表
-    """
     try:
         mcp_logger.info("收到列出工具请求")
-        
         queries = await get_queries_cache()
-        tools = []
+        tools = [generate_tool_schema_from_query(query) for query in queries]
-        
-        for query in queries:
-            tool = generate_tool_schema_from_query(query)
-            tools.append(tool)
-        
         mcp_logger.info(f"成功生成 {len(tools)} 个 MCP 工具")
         mcp_logger.debug(f"工具列表: {[tool.name for tool in tools]}")
-        
         return tools
     except Exception as e:
         mcp_logger.error(f"列出工具失败: {e}", exc_info=True)
@@ -173,151 +137,97 @@ async def handle_list_tools() -> list[types.Tool]:
 
 @server.call_tool()
 async def handle_call_tool(
-    name: str, 
+    name: str,
     arguments: dict[str, Any] | None
 ) -> list[types.TextContent]:
-    """
+    """Handle MCP tool invocation."""
-    处理工具调用请求
-    
-    Args:
-        name: 工具名称
-        arguments: 工具参数
-        
-    Returns:
-        list[types.TextContent]: 工具执行结果（返回参数和对应的接口配置）
-    """
     try:
         mcp_logger.info(f"收到工具调用请求: {name}")
         mcp_logger.debug(f"工具参数: {arguments}")
-        
+
-        # 获取查询配置缓存
         queries = await get_queries_cache()
-        
+        tool_item = next((query for query in queries if query["businessName"] == name), None)
-        # 根据工具名称查找对应的 item（接口配置）
+
-        tool_item = None
+        if not tool_item:
-        for query in queries:
+            return _text_response({"error": f"未找到工具 {name} 对应的配置"})
-            # tool_name = generate_tool_name(query['businessName'], query['id'])
+
-            tool_name = query['businessName']
+        normalized_parameters = generate_input_schema(tool_item.get("parameters"))
-            if tool_name == name:
+        normalized_arguments = arguments or {}
-                tool_item = query
+        user_id = _extract_user_id(normalized_arguments)
-                break
+
-        
+        if user_id is None:
-        # 构建返回结果
+            error_msg = f"工具 {name} 缺少必填参数 userId"
-        import json
+            mcp_logger.warning(error_msg)
-        
+            return _text_response({"error": error_msg, "required": ["userId"]})
-        if tool_item:
+
-            request_data = {
+        request_data = {
-                "datasourceId": tool_item.get("datasourceId"),
+            "datasourceId": tool_item.get("datasourceId"),
-                "businessName": tool_item.get("businessName"),
+            "businessName": tool_item.get("businessName"),
-                "businessDescription": tool_item.get("businessDescription"),
+            "businessDescription": tool_item.get("businessDescription"),
-                "sqlTemplate": tool_item.get("sqlTemplate"),
+            "sqlTemplate": tool_item.get("sqlTemplate"),
-                "parameters": tool_item.get("parameters"),
+            "parameters": normalized_parameters,
-                "testParams": arguments or {}
+            "testParams": normalized_arguments,
-            }
+            "userId": user_id
-            
+        }
-            # 如果 arguments 中有 targetDatabaseName 且有值，添加到 request_data
+
-            if arguments and arguments.get("targetDatabaseName"):
+        target_database_name = normalized_arguments.get("targetDatabaseName")
-                request_data["targetDatabaseName"] = arguments["targetDatabaseName"]
+        if target_database_name:
-                mcp_logger.debug(f"添加目标数据库名称: {arguments['targetDatabaseName']}")
+            request_data["targetDatabaseName"] = target_database_name
-            
+            mcp_logger.debug(f"添加目标数据库名称: {target_database_name}")
-            # 如果 arguments 中有 userId 且有值，添加到 request_data
+
-            if arguments and arguments.get("userId"):
+        try:
-                request_data["userId"] = arguments["userId"]
+            mcp_logger.info("正在调用测试 SQL API...")
-                mcp_logger.debug(f"添加用户ID: {arguments['userId']}")
+            result_payload = test_sql_with_schema(request_data)
-            
+            mcp_logger.info("测试 SQL API 调用成功")
-            # 调用测试SQL API
+        except Exception as e:
-            try:
+            error_msg = f"调用测试 SQL API 失败: {str(e)}"
-                mcp_logger.info("正在调用测试SQL API...")
+            mcp_logger.error(error_msg, exc_info=True)
-                api_response = test_sql_with_schema(request_data)
+            result_payload = {"error": error_msg}
-                mcp_logger.info("测试SQL API调用成功")
+
-                
+        mcp_logger.debug(f"工具调用结果: {result_payload}")
-                # 只返回 API 响应结果
+        return _text_response(result_payload)
-                result_text = json.dumps(api_response, ensure_ascii=False, indent=2)
-                
-            except Exception as e:
-                error_msg = f"调用测试SQL API失败: {str(e)}"
-                mcp_logger.error(error_msg, exc_info=True)
-                result_text = json.dumps({"error": error_msg}, ensure_ascii=False, indent=2)
-        else:
-            error_msg = f"未找到工具 {name} 对应的配置"
-            result_text = json.dumps({"error": error_msg}, ensure_ascii=False, indent=2)
-        
-        mcp_logger.debug(f"工具调用结果: {result_text}")
-        
-        return [
-            types.TextContent(
-                type="text",
-                text=result_text
-            )
-        ]
     except Exception as e:
         error_msg = f"工具调用失败: {name}, 错误: {e}"
         mcp_logger.error(error_msg, exc_info=True)
-        return [
+        return [types.TextContent(type="text", text=f"错误: {error_msg}")]
-            types.TextContent(
-                type="text",
-                text=f"错误: {error_msg}"
-            )
-        ]
 
 
 async def call_third_party_api(skill_id: str = None) -> list:
-    """
+    """Call backend API and map the response into query configs."""
-    调用第三方API获取技能信息并返回处理后的数据
-    
-    Args:
-        skill_id: 技能ID（默认从环境变量 SKILL_ID 读取，如果未设置则使用 1981000305474482178）
-        
-    Returns:
-        处理后的查询配置列表（businessQueries格式）
-        
-    Example:
-        queries = await call_third_party_api()
-        # 返回: [{"id": "...", "businessName": "...", ...}, ...]
-    """
     try:
-        # 如果没有传入 skill_id，则从环境变量读取
         if skill_id is None:
             skill_id = get_skill_id()
-        
-        mcp_logger.info(f"调用第三方API，skill_id: {skill_id}")
-        
-        # 获取原始数据
-        raw_result = get_skill_by_id(skill_id)
 
-        mcp_logger.info(f"成功{raw_result}")
+        mcp_logger.info(f"调用第三方 API，skill_id: {skill_id}")
-        
+        raw_result = get_skill_by_id(skill_id)
-        # 处理并返回
+        mcp_logger.info(f"成功获取原始响应: {raw_result}")
+
         processed_queries = process_skill_response(raw_result)
-        
+        mcp_logger.info(f"成功处理 {len(processed_queries)} 条数据")
-        mcp_logger.info(f"成功获取并处理 {len(processed_queries)} 条数据")
         return processed_queries
-        
     except Exception as e:
-        mcp_logger.error(f"API调用失败: {e}", exc_info=True)
+        mcp_logger.error(f"API 调用失败: {e}", exc_info=True)
         raise
 
 
 async def async_main():
-    """MCP 服务器异步主函数"""
+    """Async entry for the MCP server."""
     try:
         mcp_logger.info("=" * 60)
-        mcp_logger.info("正在启动 MCP 服务器: lzwcai-mcp-sqlexecutor")
+        mcp_logger.info("正在启动 MCP 服务: lzwcai-mcp-sqlexecutor")
         mcp_logger.info("版本: 0.1.0")
         mcp_logger.info("=" * 60)
-        
+
-        # 输出环境配置信息
         env_config = get_env_config()
         mcp_logger.info(f"环境配置 - Database ID: {env_config['database_id']}")
         mcp_logger.info(f"环境配置 - Skill ID: {env_config['skill_id']}")
         mcp_logger.info(f"环境配置 - Backend Base URL: {env_config['backend_base_url']}")
         mcp_logger.info("=" * 60)
-        
+
         from mcp.server.stdio import stdio_server
-        
+
         async with stdio_server() as (read_stream, write_stream):
-            mcp_logger.info("MCP 服务器已启动，等待客户端连接...")
+            mcp_logger.info("MCP 服务已启动，等待客户端连接...")
-            
             await server.run(
                 read_stream,
                 write_stream,
@@ -330,30 +240,25 @@ async def async_main():
                     ),
                 ),
             )
-            
+
-        mcp_logger.info("MCP 服务器已关闭")
+        mcp_logger.info("MCP 服务已关闭")
-        
     except Exception as e:
-        mcp_logger.error(f"MCP 服务器运行失败: {e}", exc_info=True)
+        mcp_logger.error(f"MCP 服务运行失败: {e}", exc_info=True)
         raise
 
 
 def main():
-    """入口点函数（用于 console_scripts）"""
+    """Console entrypoint."""
     try:
-        # 初始化系统日志
-        # MCP协议使用stdio通信，必须禁用控制台输出以避免干扰JSON-RPC通信
         logger_config.setup_logging(
             app_name="lzwcai_mcp_sqlexecutor",
             log_level=logging.INFO,
-            console_output=False  # 禁用控制台输出
+            console_output=False
         )
-        
+        mcp_logger.info("开始运行 MCP SQL Executor 服务")
-        mcp_logger.info("开始运行 MCP SQL Executor 服务器")
         asyncio.run(async_main())
-        
     except KeyboardInterrupt:
-        mcp_logger.info("收到中断信号，正在关闭服务器...")
+        mcp_logger.info("收到中断信号，正在关闭服务...")
     except Exception as e:
         mcp_logger.error(f"程序运行失败: {e}", exc_info=True)
         raise

lzwcai_mcp_sqlexecutor/lzwcai_mcp_sqlexecutor/utils/api_client.py

@@ -1,330 +1,209 @@
-"""
+"""Backend API client helpers."""
-第三方API调用客户端
+
-用于调用外部数据源接口
+import json
-"""
+import logging
+from typing import Any, Dict, List, Optional
 
 import httpx
-import logging
-import json
-from typing import Dict, Any, Optional, List
 
-# 支持直接运行和模块导入两种方式
 try:
     from .env_config import get_backend_base_url
 except ImportError:
     from env_config import get_backend_base_url
 
-# 获取日志记录器
+
 logger = logging.getLogger(__name__)
 
 
 class DataSourceAPIClient:
-    """数据源API客户端"""
+    """HTTP client for backend datasource APIs."""
-    
+
     def __init__(
-        self, 
+        self,
         base_url: Optional[str] = None,
         token: Optional[str] = None
     ):
-        """
-        初始化API客户端
-        
-        Args:
-            base_url: API基础URL（默认从环境变量 BACKEND_BASE_URL 读取，如果未设置则使用 http://192.168.2.236:8088）
-            token: 认证令牌（Bearer Token）
-        """
-        # 如果没有传入 base_url，则从环境变量读取
         if base_url is None:
             base_url = get_backend_base_url()
-        
+
-        self.base_url = base_url.rstrip('/')
+        self.base_url = base_url.rstrip("/")
-        self.token = token or "eyJhbGciOiJIUzUxMiJ9.eyJsb2dpbl91c2VyX2tleSI6IjJiYTk4ODllLWM2ZGItNDQ5YS1iZmFjLTQ2YzMxODFlODg5NCJ9.dvi8zm0LsWvJ_h9zD5blnHFRxa4z4_WBm1R487ekE7HlHzrN6dnvqhK8askqT5b1EcE8myHwRzLVMoI8UOjOrw"
+        self.token = token or (
+            "eyJhbGciOiJIUzUxMiJ9.eyJsb2dpbl91c2VyX2tleSI6IjJiYTk4ODllLWM2ZGItNDQ5YS1i"
+            "ZmFjLTQ2YzMxODFlODg5NCJ9.dvi8zm0LsWvJ_h9zD5blnHFRxa4z4_WBm1R487ekE7HlHzrN6dn"
+            "vqhK8askqT5b1EcE8myHwRzLVMoI8UOjOrw"
+        )
         self.client = httpx.Client(timeout=30.0)
-        
+
     def _get_headers(self) -> Dict[str, str]:
-        """
-        获取请求头
-        
-        Returns:
-            请求头字典
-        """
         return {
-            'Authorization': f'Bearer {self.token}',
+            "Authorization": f"Bearer {self.token}",
         }
-    
+
     def get_skill_by_id(self, skill_id: str) -> Dict[str, Any]:
-        """
+        """Fetch skill details by skill id."""
-        根据技能ID获取技能信息
-        
-        Args:
-            skill_id: 技能ID
-            
-        Returns:
-            API响应数据
-            
-        Raises:
-            Exception: 请求失败时抛出
-        """
         try:
             url = f"{self.base_url}/datasource/skill/getBySkillId/{skill_id}"
-            
+
-            logger.info(f"正在调用API: {url}")
+            logger.info(f"正在调用 API: {url}")
             logger.debug(f"请求参数 - skill_id: {skill_id}")
-            
+
-            response = self.client.get(
+            response = self.client.get(url, headers=self._get_headers())
-                url,
-                headers=self._get_headers()
-            )
-            
-            # 检查HTTP状态码
             response.raise_for_status()
-            
-            # 解析JSON响应
             data = response.json()
-            
+
-            logger.info(f"API调用成功: {url}")
+            logger.info(f"API 调用成功: {url}")
             logger.debug(f"响应数据: {data}")
-            
             return data
-            
+
         except httpx.TimeoutException:
-            error_msg = f"API请求超时: {url}"
+            error_msg = f"API 请求超时: {url}"
             logger.error(error_msg)
             raise Exception(error_msg)
-            
         except httpx.HTTPStatusError as e:
-            error_msg = f"API请求失败 (HTTP {e.response.status_code}): {url}"
+            error_msg = f"API 请求失败 (HTTP {e.response.status_code}): {url}"
             logger.error(error_msg)
             logger.error(f"错误响应: {e.response.text}")
             raise Exception(error_msg)
-            
         except httpx.RequestError as e:
-            error_msg = f"API请求异常: {url}, 错误: {str(e)}"
+            error_msg = f"API 请求异常: {url}, 错误: {str(e)}"
             logger.error(error_msg)
             raise Exception(error_msg)
-            
         except Exception as e:
-            error_msg = f"处理API响应时出错: {str(e)}"
+            error_msg = f"处理 API 响应时出错: {str(e)}"
             logger.error(error_msg, exc_info=True)
             raise Exception(error_msg)
-    
+
     def test_sql_with_schema(self, request_data: Dict[str, Any]) -> Dict[str, Any]:
-        """
+        """Call backend SQL test endpoint."""
-        测试SQL语句并返回执行结果
-        
-        Args:
-            request_data: 请求数据，包含以下字段：
-                - datasourceId: 数据源ID
-                - businessName: 业务名称
-                - businessDescription: 业务描述
-                - sqlTemplate: SQL模板
-                - parameters: 参数定义
-                - testParams: 测试参数
-                
-        Returns:
-            API响应数据
-            
-        Raises:
-            Exception: 请求失败时抛出
-        """
         try:
-            # 详细记录传入的数据
             logger.info("=" * 80)
             logger.info("test_sql_with_schema 接口接收到的数据:")
             logger.info(f"数据类型: {type(request_data)}")
             logger.info(f"数据内容: {json.dumps(request_data, ensure_ascii=False, indent=2)}")
-            logger.info(f"数据源ID: {request_data.get('datasourceId')}")
+            logger.info(f"数据源 ID: {request_data.get('datasourceId')}")
             logger.info(f"业务名称: {request_data.get('businessName')}")
             logger.info(f"业务描述: {request_data.get('businessDescription')}")
-            logger.info(f"SQL模板: {request_data.get('sqlTemplate')}")
+            logger.info(f"SQL 模板: {request_data.get('sqlTemplate')}")
             logger.info(f"参数定义: {request_data.get('parameters')}")
             logger.info(f"测试参数: {request_data.get('testParams')}")
-            if 'userId' in request_data:
+            if "userId" in request_data:
-                logger.info(f"用户ID: {request_data.get('userId')}")
+                logger.info(f"用户 ID: {request_data.get('userId')}")
             logger.info("=" * 80)
-            
+
             url = f"{self.base_url}/datasource/sqlExecutionLog/testSqlWithSchema"
-            
-            # 构建请求头（包含Content-Type）
             headers = self._get_headers()
-            headers['Content-Type'] = 'application/json'
+            headers["Content-Type"] = "application/json"
-            headers['Accept'] = '*/*'
+            headers["Accept"] = "*/*"
-            
+
-            logger.info(f"正在调用测试SQL API: {url}")
+            logger.info(f"正在调用测试 SQL API: {url}")
             logger.debug(f"请求数据: {json.dumps(request_data, ensure_ascii=False, indent=2)}")
-            
+
-            # 发送POST请求
+            response = self.client.post(url, headers=headers, json=request_data)
-            response = self.client.post(
-                url,
-                headers=headers,
-                json=request_data
-            )
-            
-            # 检查HTTP状态码
             response.raise_for_status()
-            
-            # 解析JSON响应
             data = response.json()
-            
+
-            # 详细记录返回的数据
             logger.info("=" * 80)
             logger.info("test_sql_with_schema 接口返回的数据:")
-            logger.info(f"HTTP状态码: {response.status_code}")
+            logger.info(f"HTTP 状态码: {response.status_code}")
             logger.info(f"响应数据类型: {type(data)}")
             logger.info(f"响应数据内容: {json.dumps(data, ensure_ascii=False, indent=2)}")
             if isinstance(data, dict):
-                logger.info(f"响应code: {data.get('code')}")
+                logger.info(f"响应 code: {data.get('code')}")
-                logger.info(f"响应msg: {data.get('msg')}")
+                logger.info(f"响应 msg: {data.get('msg')}")
-                logger.info(f"响应data: {data.get('data')}")
+                logger.info(f"响应 data: {data.get('data')}")
             logger.info("=" * 80)
-            
+
-            logger.info("测试SQL API调用成功")
+            logger.info("测试 SQL API 调用成功")
-            
             return data
-            
+
         except httpx.TimeoutException:
-            error_msg = f"测试SQL API请求超时: {url}"
+            error_msg = f"测试 SQL API 请求超时: {url}"
             logger.error(error_msg)
             raise Exception(error_msg)
-            
         except httpx.HTTPStatusError as e:
-            error_msg = f"测试SQL API请求失败 (HTTP {e.response.status_code}): {url}"
+            error_msg = f"测试 SQL API 请求失败 (HTTP {e.response.status_code}): {url}"
             logger.error(error_msg)
             logger.error(f"错误响应: {e.response.text}")
             raise Exception(error_msg)
-            
         except httpx.RequestError as e:
-            error_msg = f"测试SQL API请求异常: {url}, 错误: {str(e)}"
+            error_msg = f"测试 SQL API 请求异常: {url}, 错误: {str(e)}"
             logger.error(error_msg)
             raise Exception(error_msg)
-            
         except Exception as e:
-            error_msg = f"处理测试SQL API响应时出错: {str(e)}"
+            error_msg = f"处理测试 SQL API 响应时出错: {str(e)}"
             logger.error(error_msg, exc_info=True)
             raise Exception(error_msg)
-    
+
     def close(self):
-        """关闭HTTP客户端"""
+        """Close the underlying HTTP client."""
         self.client.close()
 
 
-# 创建默认客户端实例
 default_client = DataSourceAPIClient()
 
 
-def get_skill_by_id(skill_id: str, base_url: Optional[str] = None, token: Optional[str] = None) -> Dict[str, Any]:
+def get_skill_by_id(
-    """
+    skill_id: str,
-    便捷函数：根据技能ID获取技能信息
+    base_url: Optional[str] = None,
-    
+    token: Optional[str] = None
-    Args:
+) -> Dict[str, Any]:
-        skill_id: 技能ID
+    """Convenience wrapper for skill lookup."""
-        base_url: API基础URL（可选，默认从环境变量 BACKEND_BASE_URL 读取）
-        token: 认证令牌（可选，使用默认值）
-        
-    Returns:
-        API响应数据
-    """
     if base_url or token:
-        client = DataSourceAPIClient(
+        client = DataSourceAPIClient(base_url=base_url, token=token)
-            base_url=base_url,
-            token=token
-        )
         return client.get_skill_by_id(skill_id)
-    else:
+    return default_client.get_skill_by_id(skill_id)
-        return default_client.get_skill_by_id(skill_id)
 
 
-def test_sql_with_schema(request_data: Dict[str, Any], base_url: Optional[str] = None, token: Optional[str] = None) -> Dict[str, Any]:
+def test_sql_with_schema(
-    """
+    request_data: Dict[str, Any],
-    便捷函数：测试SQL语句并返回执行结果
+    base_url: Optional[str] = None,
-    
+    token: Optional[str] = None
-    Args:
+) -> Dict[str, Any]:
-        request_data: 请求数据，包含以下字段：
+    """Convenience wrapper for SQL test endpoint."""
-            - datasourceId: 数据源ID
-            - businessName: 业务名称
-            - businessDescription: 业务描述
-            - sqlTemplate: SQL模板
-            - parameters: 参数定义
-            - testParams: 测试参数
-        base_url: API基础URL（可选，默认从环境变量 BACKEND_BASE_URL 读取）
-        token: 认证令牌（可选，使用默认值）
-        
-    Returns:
-        API响应数据
-    """
     if base_url or token:
-        client = DataSourceAPIClient(
+        client = DataSourceAPIClient(base_url=base_url, token=token)
-            base_url=base_url,
-            token=token
-        )
         return client.test_sql_with_schema(request_data)
-    else:
+    return default_client.test_sql_with_schema(request_data)
-        return default_client.test_sql_with_schema(request_data)
 
 
 def process_skill_response(response: Dict[str, Any]) -> List[Dict[str, Any]]:
-    """
+    """Map backend skill response into business query configs."""
-    处理API响应数据，映射为businessQueries格式
-    
-    Args:
-        response: API原始响应数据
-        
-    Returns:
-        处理后的查询配置列表
-    """
     try:
-        # 提取data数组
         data_list = response.get("data", [])
-        
-        # 默认的员工ID参数schema
-        default_employee_schema = {
-            "type": "object",
-            "required": ["employeeId"],
-            "properties": {
-                "employeeId": {
-                    "type": "number",
-                    "description": "员工ID，用于标识员工的唯一数字标识符",
-                    "examples": [1001, 2002]
-                }
-            }
-        }
-        
-        # 映射每个skill为businessQuery格式
         queries = []
+
         for skill in data_list:
-            # 解析sqlParams字符串为JSON对象
+            sql_params_raw = skill.get("sqlParams")
-            sql_params_str = skill.get("sqlParams") or "{}"
+            sql_params: Dict[str, Any] = {}
-            sql_params = json.loads(sql_params_str)
+
-            
+            if isinstance(sql_params_raw, dict):
-            # 判断sqlParams是否为空对象
+                sql_params = sql_params_raw
-            is_empty_params = (
+            elif isinstance(sql_params_raw, str) and sql_params_raw.strip():
-                not sql_params.get("properties") or 
+                try:
-                len(sql_params.get("properties", {})) == 0
+                    parsed_sql_params = json.loads(sql_params_raw)
-            ) and (
+                    if isinstance(parsed_sql_params, dict):
-                not sql_params.get("required") or 
+                        sql_params = parsed_sql_params
-                len(sql_params.get("required", [])) == 0
+                    else:
-            )
+                        logger.warning(
-            
+                            f"技能 {skill.get('name')} (ID: {skill.get('id')}) 的 sqlParams 不是对象，已回退为空对象"
-            # # 如果是空对象，使用默认的员工ID参数
+                        )
-            # if is_empty_params:
+                except json.JSONDecodeError:
-            #     logger.info(f"技能 {skill.get('name')} (ID: {skill.get('id')}) 的sqlParams为空，使用默认员工ID参数")
+                    logger.warning(
-            #     sql_params = default_employee_schema
+                        f"技能 {skill.get('name')} (ID: {skill.get('id')}) 的 sqlParams 不是合法 JSON，已回退为空对象"
-            
+                    )
-            # 映射字段
+
             query = {
                 "id": skill.get("id"),
                 "businessName": skill.get("name"),
                 "businessDescription": skill.get("description"),
                 "sqlTemplate": skill.get("sqlTemplate"),
                 "parameters": sql_params,
-                "datasourceId": skill.get("datasourceId")
+                "datasourceId": skill.get("datasourceId"),
             }
             queries.append(query)
-        
+
         logger.info(f"成功处理 {len(queries)} 条技能数据")
         return queries
-        
     except Exception as e:
-        logger.error(f"处理API响应数据失败: {e}", exc_info=True)
+        logger.error(f"处理 API 响应数据失败: {e}", exc_info=True)
         raise
-

lzwcai_mcp_sqlexecutor/lzwcai_mcp_sqlexecutor/utils/schema_helper.py

@@ -1,149 +1,93 @@
 # -*- coding: utf-8 -*-
 """
-Schema 生成工具模块
+Schema 生成工具模块。
 """
 
+from copy import deepcopy
 from typing import Any, Dict
 
 
-def generate_input_schema(parameters: Dict[str, Any]) -> Dict[str, Any]:
+def _normalize_schema(parameters: Dict[str, Any] | None) -> Dict[str, Any]:
-    """
+    """将任意参数定义归一化为 object schema。"""
-    从查询配置的参数定义生成 MCP 工具的 inputSchema
+    if not isinstance(parameters, dict) or not parameters:
-    
-    此函数会保留完整的 JSON Schema 信息，包括：
-    - type: Schema 类型（通常是 "object"）
-    - required: 必填字段列表
-    - properties: 属性定义（包括每个属性的 type, description, format, examples 等）
-    - description: Schema 的整体描述（如果有）
-    - 以及其他任何 JSON Schema 标准字段
-    
-    此函数还会自动添加以下字段（如果原始 parameters 中未定义）：
-    - targetDatabaseName: 目标数据库名称（非必填，默认为空字符串）
-    
-    Args:
-        parameters: 查询配置中的参数定义字典，应该是一个完整的 JSON Schema 对象
-        
-    Returns:
-        Dict[str, Any]: 符合 JSON Schema 规范的 inputSchema 对象
-        
-    Example:
-        >>> params = {
-        ...     "type": "object",
-        ...     "required": ["userId", "startTime"],
-        ...     "properties": {
-        ...         "userId": {
-        ...             "type": "integer",
-        ...             "description": "用户的唯一标识符",
-        ...             "examples": [10086]
-        ...         },
-        ...         "startTime": {
-        ...             "type": "string",
-        ...             "format": "date-time",
-        ...             "description": "查询的起始时间",
-        ...             "examples": ["2023-01-01 00:00:00"]
-        ...         }
-        ...     }
-        ... }
-        >>> schema = generate_input_schema(params)
-        >>> # schema 将包含所有原始信息，包括 format 和 examples
-        >>> # 同时会自动添加 targetDatabaseName 字段
-    """
-    # 如果 parameters 本身就是一个完整的 JSON Schema 对象，直接使用
-    # 但确保至少包含 type 和 properties
-    if not parameters:
-        # 如果 parameters 为空，返回一个空的 object schema
         return {
             "type": "object",
             "properties": {},
             "required": []
         }
-    
+
-    # 深拷贝 parameters 以避免修改原始数据
+    input_schema = deepcopy(parameters)
-    input_schema = dict(parameters)
+    input_schema["type"] = "object"
-    
+
-    # 确保必需的字段存在
+    if not isinstance(input_schema.get("properties"), dict):
-    if "type" not in input_schema:
-        input_schema["type"] = "object"
-    
-    if "properties" not in input_schema:
         input_schema["properties"] = {}
-    
+
-    if "required" not in input_schema:
+    if not isinstance(input_schema.get("required"), list):
         input_schema["required"] = []
-    
+
-    # 添加 targetDatabaseName 字段（如果不存在）
+    return input_schema
+
+
+def generate_input_schema(parameters: Dict[str, Any] | None) -> Dict[str, Any]:
+    """
+    从查询配置的参数定义生成 MCP 工具的 inputSchema。
+
+    会统一补齐：
+    - `targetDatabaseName`：可选
+    - `userId`：必填
+    """
+    input_schema = _normalize_schema(parameters)
+
     if "targetDatabaseName" not in input_schema["properties"]:
         input_schema["properties"]["targetDatabaseName"] = {
             "type": "string",
             "description": "目标数据库名称",
             "default": ""
         }
-    
+
-    # 添加 userId 字段（如果不存在）
     if "userId" not in input_schema["properties"]:
         input_schema["properties"]["userId"] = {
             "type": "string",
-            "description": "当前ai平台用户id；"
+            "description": "当前 AI 平台用户 ID"
         }
-    
+
-    # 保留所有其他字段，如 description, examples, format 等
+    if "userId" not in input_schema["required"]:
-    # JSON Schema 标准支持的字段都会被保留：
+        input_schema["required"].append("userId")
-    # - additionalProperties
+
-    # - patternProperties
-    # - minProperties / maxProperties
-    # - dependencies
-    # - 等等
-    
     return input_schema
 
 
 def validate_input_schema(schema: Dict[str, Any]) -> tuple[bool, str]:
     """
-    验证 inputSchema 是否符合基本的 JSON Schema 规范
+    验证 inputSchema 是否符合基本的 JSON Schema 规范。
-    
-    Args:
-        schema: 要验证的 schema 对象
-        
-    Returns:
-        tuple[bool, str]: (是否有效, 错误消息或成功消息)
-        
-    Example:
-        >>> schema = {"type": "object", "properties": {"id": {"type": "string"}}}
-        >>> is_valid, msg = validate_input_schema(schema)
-        >>> print(is_valid, msg)
-        True, "Schema 验证通过"
     """
     if not isinstance(schema, dict):
         return False, "Schema 必须是一个字典对象"
-    
+
     if schema.get("type") != "object":
         return False, "Schema 的 type 字段必须是 'object'"
-    
+
     if "properties" not in schema:
         return False, "Schema 必须包含 properties 字段"
-    
+
     if not isinstance(schema.get("properties"), dict):
         return False, "Schema 的 properties 字段必须是一个字典对象"
-    
+
-    # 验证 required 字段（如果存在）
     if "required" in schema:
         required = schema["required"]
         if not isinstance(required, list):
             return False, "Schema 的 required 字段必须是一个列表"
-        
+
-        # 验证所有 required 的字段都在 properties 中定义
         properties = schema["properties"]
         for field in required:
             if field not in properties:
                 return False, f"必填字段 '{field}' 未在 properties 中定义"
-    
+
-    # 验证 properties 中每个字段的定义
     for prop_name, prop_def in schema["properties"].items():
         if not isinstance(prop_def, dict):
             return False, f"属性 '{prop_name}' 的定义必须是一个字典对象"
-        
+
         if "type" not in prop_def:
             return False, f"属性 '{prop_name}' 必须包含 type 字段"
-    
-    return True, "Schema 验证通过"
 
+    return True, "Schema 验证通过"

lzwcai_mcp_sqlexecutor/main.py

@@ -1,14 +1,20 @@
 """
-Entry point for lzwcai-mcp-sqlexecutor
+Repository-local launcher for lzwcai-mcp-sqlexecutor.
-Runs the MCP server for SQL query execution
 """
+
 import os
 
-os.environ["databaseId"] = "162"
-os.environ["skillId"] = "2008360664955854850"
-os.environ["backendBaseUrl"] = "http://192.168.2.236:8088"
-if __name__ == "__main__":
-    # Import and run the actual MCP server
-    from lzwcai_mcp_sqlexecutor.main import main
 
+def main():
+    # Keep local developer defaults without overriding explicit environment settings.
+    os.environ.setdefault("databaseId", "240")
+    os.environ.setdefault("skillId", "2058819964077572098")
+    os.environ.setdefault("backendBaseUrl", "http://192.168.2.236:8088")
+
+    from lzwcai_mcp_sqlexecutor.main import main as package_main
+
+    package_main()
+
+
+if __name__ == "__main__":
     main()

lzwcai_mcp_sqlexecutor/pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "hatchling.build"
 
 [project]
 name = "lzwcai-mcp-sqlexecutor"
-version = "0.1.12"
+version = "0.1.13"
 description = "MCP server for executing business SQL queries with dynamic tool generation"
 readme = "README.md"
 requires-python = ">=3.10"

lzwcai_workflow_to_mcp/lzwcai_workflow_to_mcp/utils/api_client.py

@@ -24,7 +24,7 @@ WORKFLOW_EXECUTE_TIMEOUT = 600.0  # 工作流执行超时（10分钟，参考 wo
 
 # 异步轮询默认配置（参考 workflow-execution-api.md）
 DEFAULT_POLLING_INTERVAL = 1.0
-DEFAULT_MAX_POLL_COUNT = 120
+DEFAULT_MAX_POLL_COUNT = 800
 DEFAULT_MAX_ERROR_COUNT = 3
 
 

lzwcai_workflow_to_mcp/pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "hatchling.build"
 
 [project]
 name = "lzwcai-workflow-to-mcp"
-version = "0.1.8"
+version = "0.1.9"
 description = "MCP server for executing business SQL queries with dynamic tool generation"
 readme = "README.md"
 requires-python = ">=3.10"