feat(lzwcai-workflow-to-mcp): 初始化项目并实现动态 MCP 工具生成功能
- 添加 Python 3.13 版本声明文件 `.python-version` - 新增 `businessQueries.json`，包含三个 SQL 查询配置：按摘要、科目查凭证及科目余额 - 实现主程序 `main.py` 支持 local 和 api 两种模式加载配置，并注册为 MCP Server 工具 - 创建 `schema_converter.py` 用于将 sqlParams 转换为 MCP 输入 schema - 配置 `pyproject.toml` 定义项目元数据与依赖（mcp, anyio, requests） - 引入 utils 包结构，支持 API 请求、环境变量读取、日志配置等辅助功能模块 - 提供完整的工具列表和调用逻辑，通过 stdio 与 MCP 客户端通信执行工作流
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[
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{
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"id": "2000851983567065089",
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"createBy": "bjt",
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"createTime": "2025-12-16 16:54:22",
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"updateBy": null,
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"updateTime": null,
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"serviceId": "2000821852159709186",
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"uniqueName": "按摘要查凭证",
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"name": "anzhaiyaochapingzheng_91da19f8",
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"description": "按照摘要描述查询凭证信息",
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"visualizable": 1,
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"toolPrompt": "按照摘要描述查询凭证信息",
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"toolType": "sql",
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"datasourceId": "158",
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"sqlTemplate": "WITH query_params AS (\n SELECT \n {year}::INT AS target_year,\n '{digest}' AS digest_keyword,\n '{company_names}' AS company_names_param,\n '{months}' AS months_param\n),\ncompany_filters AS (\n SELECT \n TRIM(keyword) AS company_keyword\n FROM (\n SELECT unnest(string_to_array(nullif((SELECT company_names_param FROM query_params LIMIT 1), ''), ',')) AS keyword\n ) t\n WHERE keyword IS NOT NULL AND TRIM(keyword) <> ''\n),\nmonth_filters AS (\n SELECT \n month::INT AS target_month\n FROM (\n SELECT unnest(string_to_array(nullif((SELECT months_param FROM query_params LIMIT 1), ''), ',')) AS month\n ) t\n WHERE month IS NOT NULL AND TRIM(month) <> ''\n)\n\nSELECT \n c.company_name AS 公司,\n v.dbill_date AS 日期,\n v.csign || LPAD(v.ino_id::text, 4, '0') AS 凭证号,\n v.cdigest AS 摘要,\n a.ccode AS 科目编码,\n a.ccode_name AS 科目名称,\n v.md AS 借方,\n v.mc AS 贷方,\n v.cbill AS 制单人\nFROM uf_voucher v\nJOIN uf_company c ON v.company_id = c.id\nJOIN uf_account_code a ON v.account_code_id = a.id\nCROSS JOIN query_params qp\nWHERE v.bdelete = false\n AND v.iyear = qp.target_year\n AND v.cdigest LIKE '%' || qp.digest_keyword || '%'\n AND (\n NOT EXISTS (SELECT 1 FROM company_filters)\n OR EXISTS (\n SELECT 1 FROM company_filters cf \n WHERE c.company_name LIKE '%' || cf.company_keyword || '%'\n )\n )\n AND (\n NOT EXISTS (SELECT 1 FROM month_filters)\n OR v.iperiod IN (SELECT target_month FROM month_filters)\n )\nORDER BY c.company_name, v.dbill_date DESC, v.ino_id;",
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"sqlParams": "[{\"type\":\"paragraph\",\"name\":\"digest\",\"displayName\":\"摘要关键字\",\"maxLength\":500,\"defaultValue\":\"\",\"required\":true},{\"type\":\"string\",\"name\":\"company_names\",\"displayName\":\"公司名称\",\"maxLength\":200,\"defaultValue\":\"\",\"required\":false},{\"type\":\"number\",\"name\":\"year\",\"displayName\":\"会计年度\",\"maxLength\":4,\"defaultValue\":\"2025\",\"required\":true},{\"type\":\"string\",\"name\":\"months\",\"displayName\":\"月份\",\"maxLength\":50,\"defaultValue\":\"\",\"required\":false}]",
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"resultType": "list",
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"sourceType": "ai",
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|
"trainingTaskId": null,
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|
"tableMetadataIds": "",
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"executionCount": 0,
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"visualizationConfigs": [],
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"inputJsonSchema": "{}",
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"outputJsonSchema": "{\"type\":\"object\",\"properties\":{\"data\":{\"type\":\"array\"}}}",
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"lastExecutionTime": null
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},
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{
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"id": "2000852304343240706",
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"createBy": "bjt",
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"createTime": "2025-12-16 16:55:38",
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"updateBy": null,
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"updateTime": null,
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"serviceId": "2000821852159709186",
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"uniqueName": "按科目查凭证",
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"name": "ankemuchapingzheng_6a268ea1",
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"description": "按照科目名称查询凭证信息",
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"visualizable": 1,
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"toolPrompt": "按照科目名称查询凭证信息",
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"toolType": "sql",
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"datasourceId": "158",
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"sqlTemplate": "WITH query_params AS (\n SELECT \n {year}::INT AS target_year,\n '{company_names}' AS company_names_param,\n '{subject_name}' AS subject_keyword,\n '{months}' AS months_param\n),\ncompany_filters AS (\n SELECT \n TRIM(keyword) AS company_keyword\n FROM (\n SELECT unnest(string_to_array(nullif((SELECT company_names_param FROM query_params LIMIT 1), ''), ',')) AS keyword\n ) t\n WHERE keyword IS NOT NULL AND TRIM(keyword) <> ''\n),\nmonth_filters AS (\n SELECT \n month::INT AS target_month\n FROM (\n SELECT unnest(string_to_array(nullif((SELECT months_param FROM query_params LIMIT 1), ''), ',')) AS month\n ) t\n WHERE month IS NOT NULL AND TRIM(month) <> ''\n),\n目标科目 AS (\n SELECT DISTINCT a.id, a.ccode\n FROM uf_account_code a\n JOIN uf_company c ON a.company_id = c.id\n CROSS JOIN query_params qp\n WHERE a.ccode_name LIKE '%' || qp.subject_keyword || '%'\n AND a.iyear = qp.target_year\n AND (\n NOT EXISTS (SELECT 1 FROM company_filters)\n OR EXISTS (\n SELECT 1 FROM company_filters cf \n WHERE c.company_name LIKE '%' || cf.company_keyword || '%'\n )\n )\n),\n相关科目 AS (\n SELECT a.id\n FROM uf_account_code a\n JOIN uf_company c ON a.company_id = c.id\n CROSS JOIN query_params qp\n WHERE a.iyear = qp.target_year\n AND EXISTS (\n SELECT 1 FROM 目标科目 t \n WHERE a.ccode LIKE t.ccode || '%'\n )\n AND (\n NOT EXISTS (SELECT 1 FROM company_filters)\n OR EXISTS (\n SELECT 1 FROM company_filters cf \n WHERE c.company_name LIKE '%' || cf.company_keyword || '%'\n )\n )\n)\nSELECT \n c.company_name AS 公司,\n v.dbill_date AS 日期,\n v.csign || LPAD(v.ino_id::text, 4, '0') AS 凭证号,\n v.cdigest AS 摘要,\n a.ccode AS 科目编码,\n a.ccode_name AS 科目名称,\n a.igrade AS 级次,\n v.md AS 借方,\n v.mc AS 贷方\nFROM uf_voucher v\nJOIN uf_company c ON v.company_id = c.id\nJOIN uf_account_code a ON v.account_code_id = a.id\nCROSS JOIN query_params qp\nWHERE v.bdelete = false\n AND v.account_code_id IN (SELECT id FROM 相关科目)\n AND v.iyear = qp.target_year\n AND (\n NOT EXISTS (SELECT 1 FROM company_filters)\n OR EXISTS (\n SELECT 1 FROM company_filters cf \n WHERE c.company_name LIKE '%' || cf.company_keyword || '%'\n )\n )\n AND (\n NOT EXISTS (SELECT 1 FROM month_filters)\n OR v.iperiod IN (SELECT target_month FROM month_filters)\n )\nORDER BY c.company_name, a.ccode, v.dbill_date, v.ino_id;",
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"sqlParams": "[{\"type\":\"select\",\"name\":\"subject_name\",\"displayName\":\"科目名称\",\"maxLength\":100,\"defaultValue\":\"\",\"required\":true,\"options\":[\"管理费用\",\"销售费用\",\"财务费用\",\"应收账款\",\"应付账款\"]},{\"type\":\"paragraph\",\"name\":\"company_names\",\"displayName\":\"公司名称列表\",\"maxLength\":300,\"defaultValue\":\"\",\"required\":false},{\"type\":\"number\",\"name\":\"year\",\"displayName\":\"年度\",\"maxLength\":4,\"defaultValue\":\"2025\",\"required\":true},{\"type\":\"select\",\"name\":\"months\",\"displayName\":\"期间月份\",\"maxLength\":30,\"defaultValue\":\"\",\"required\":false,\"options\":[\"1\",\"2\",\"3\",\"4\",\"5\",\"6\",\"7\",\"8\",\"9\",\"10\",\"11\",\"12\"]}]",
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|
"resultType": "list",
|
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|
"sourceType": "ai",
|
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|
"trainingTaskId": null,
|
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|
"tableMetadataIds": "",
|
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|
"executionCount": 0,
|
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|
"visualizationConfigs": [],
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|
"inputJsonSchema": "{}",
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|
"outputJsonSchema": "{\"type\":\"object\",\"properties\":{\"data\":{\"type\":\"array\"}}}",
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|
"lastExecutionTime": null
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|
},
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|
{
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|
"id": "2000852610904920066",
|
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|
"createBy": "bjt",
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|
"createTime": "2025-12-16 16:56:51",
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|
"updateBy": null,
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"updateTime": null,
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|
"serviceId": "2000821852159709186",
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"uniqueName": "按科目查余额",
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"name": "ankemuchayue_68b302c2",
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"description": "按照科目名称查询余额",
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"visualizable": 1,
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"toolPrompt": "按照科目名称查询余额",
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"toolType": "sql",
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"datasourceId": "158",
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"sqlTemplate": "WITH query_params AS (\n SELECT \n {year}::INT AS target_year,\n '{company_names}' AS company_names_param,\n '{subject_name}' AS subject_keyword,\n '{months}' AS months_param\n),\ncompany_filters AS (\n SELECT \n TRIM(keyword) AS company_keyword\n FROM (\n SELECT unnest(string_to_array(nullif((SELECT company_names_param FROM query_params LIMIT 1), ''), ',')) AS keyword\n ) t\n WHERE keyword IS NOT NULL AND TRIM(keyword) <> ''\n),\nmonth_filters AS (\n SELECT \n month::INT AS target_month\n FROM (\n SELECT unnest(string_to_array(nullif((SELECT months_param FROM query_params LIMIT 1), ''), ',')) AS month\n ) t\n WHERE month IS NOT NULL AND TRIM(month) <> ''\n),\n目标科目 AS (\n SELECT DISTINCT a.id, a.ccode\n FROM uf_account_code a\n JOIN uf_company c ON a.company_id = c.id\n CROSS JOIN query_params qp\n WHERE a.ccode_name LIKE '%' || qp.subject_keyword || '%'\n AND a.iyear = qp.target_year\n AND (\n NOT EXISTS (SELECT 1 FROM company_filters)\n OR EXISTS (\n SELECT 1 FROM company_filters cf \n WHERE c.company_name LIKE '%' || cf.company_keyword || '%'\n )\n )\n),\n相关科目 AS (\n SELECT a.id\n FROM uf_account_code a\n JOIN uf_company c ON a.company_id = c.id\n CROSS JOIN query_params qp\n WHERE a.iyear = qp.target_year\n AND EXISTS (\n SELECT 1 FROM 目标科目 t \n WHERE a.ccode LIKE t.ccode || '%'\n )\n AND (\n NOT EXISTS (SELECT 1 FROM company_filters)\n OR EXISTS (\n SELECT 1 FROM company_filters cf \n WHERE c.company_name LIKE '%' || cf.company_keyword || '%'\n )\n )\n)\nSELECT \n c.company_name AS 公司,\n a.ccode AS 科目编码,\n a.ccode_name AS 科目名称,\n a.igrade AS 级次,\n a.cclass AS 类别,\n b.iyear AS 年,\n b.iperiod AS 月,\n b.cbegind_c AS 期初方向,\n b.mb AS 期初余额,\n b.md AS 借方发生,\n b.mc AS 贷方发生,\n b.cendd_c AS 期末方向,\n b.me AS 期末余额\nFROM uf_account_balance b\nJOIN uf_company c ON b.company_id = c.id\nJOIN uf_account_code a ON b.account_code_id = a.id\nCROSS JOIN query_params qp\nWHERE b.iyear = qp.target_year\n AND b.account_code_id IN (SELECT id FROM 相关科目)\n AND (\n NOT EXISTS (SELECT 1 FROM company_filters)\n OR EXISTS (\n SELECT 1 FROM company_filters cf \n WHERE c.company_name LIKE '%' || cf.company_keyword || '%'\n )\n )\n AND (\n NOT EXISTS (SELECT 1 FROM month_filters)\n OR b.iperiod IN (SELECT target_month FROM month_filters)\n )\nORDER BY c.company_name, a.ccode, b.iperiod;",
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"sqlParams": "[{\"type\":\"string\",\"name\":\"subject_name\",\"displayName\":\"科目名称关键字\",\"maxLength\":100,\"defaultValue\":\"银行存款\",\"required\":true},{\"type\":\"string\",\"name\":\"company_names\",\"displayName\":\"公司筛选\",\"maxLength\":150,\"defaultValue\":\"\",\"required\":false},{\"type\":\"number\",\"name\":\"year\",\"displayName\":\"查询年度\",\"maxLength\":4,\"defaultValue\":\"2025\",\"required\":true},{\"type\":\"number\",\"name\":\"months\",\"displayName\":\"查询月份\",\"maxLength\":2,\"defaultValue\":\"\",\"required\":false}]",
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"resultType": "list",
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|
"sourceType": "ai",
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|
"trainingTaskId": null,
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"tableMetadataIds": "",
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"executionCount": 0,
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"visualizationConfigs": [],
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"inputJsonSchema": "{}",
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|
"outputJsonSchema": "{\"type\":\"object\",\"properties\":{\"data\":{\"type\":\"array\"}}}",
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"lastExecutionTime": null
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}
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|
]
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296
lzwcai_workflow_to_mcp/lzwcai_workflow_to_mcp/main.py
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296
lzwcai_workflow_to_mcp/lzwcai_workflow_to_mcp/main.py
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#!/usr/bin/env python3
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"""
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Workflow to MCP Server
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从 businessQueries.json 或 API 动态生成 MCP 工具
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支持两种模式:
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- local: 从本地 JSON 文件加载
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- api: 从远程 API 加载
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"""
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import json
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import os
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import logging
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import argparse
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import anyio
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import mcp.types as types
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from mcp.server import NotificationOptions, Server
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from mcp.server.models import InitializationOptions
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from mcp.server.stdio import stdio_server
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try:
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from .schema_converter import convert_sql_params_to_input_schema
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from .utils.api_client import execute_workflow, get_workflow_by_id
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from .utils.env_config import get_workflow_id
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from .utils.logger_config import setup_system_logging, get_logger
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except ImportError:
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from schema_converter import convert_sql_params_to_input_schema
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from utils.api_client import execute_workflow, get_workflow_by_id
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from utils.env_config import get_workflow_id
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from utils.logger_config import setup_system_logging, get_logger
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# 初始化日志系统
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setup_system_logging(app_name="lzwcai_workflow_to_mcp", log_level=logging.DEBUG)
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logger = get_logger(__name__)
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# 初始化 MCP Server
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server = Server("workflow_mcp_server")
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# 全局配置
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_tools_config: list[dict] = []
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_config: dict = {}
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def parse_arguments():
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"""解析命令行参数"""
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parser = argparse.ArgumentParser(description="Workflow MCP Server")
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parser.add_argument(
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"--mode",
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type=str,
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choices=["local", "api"],
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default="api",
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help="数据加载模式: local(本地JSON) 或 api(远程API，默认)"
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)
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parser.add_argument(
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"--json-path",
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type=str,
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default=None,
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help="本地 JSON 文件路径 (local 模式)"
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)
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parser.add_argument(
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"--workflow-id",
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type=str,
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default=None,
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help="工作流ID (api 模式，可选，默认从环境变量 workflowId 获取)"
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)
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return parser.parse_args()
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class DataLoader:
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"""数据加载器基类"""
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def load(self) -> list[dict]:
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raise NotImplementedError
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class LocalLoader(DataLoader):
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"""本地 JSON 文件加载器"""
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def __init__(self, json_path: str = None):
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if json_path is None:
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json_path = os.path.join(os.path.dirname(__file__), "businessQueries.json")
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self.json_path = json_path
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|
def load(self) -> list[dict]:
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try:
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with open(self.json_path, "r", encoding="utf-8") as f:
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data = json.load(f)
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logger.info(f"从本地加载 {len(data)} 条配置: {self.json_path}")
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return data
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except FileNotFoundError:
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logger.error(f"配置文件不存在: {self.json_path}")
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return []
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except json.JSONDecodeError as e:
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logger.error(f"JSON 解析错误: {e}")
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return []
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class ApiLoader(DataLoader):
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"""API 远程加载器 - 使用 get_workflow_by_id 获取工作流配置"""
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def __init__(self, workflow_id: str = None):
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self.workflow_id = workflow_id or get_workflow_id()
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logger.debug(f"ApiLoader 初始化，工作流ID: {self.workflow_id}")
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def load(self) -> list[dict]:
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try:
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if not self.workflow_id:
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logger.error("未提供工作流ID，请设置环境变量 workflowId")
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return []
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logger.info(f"开始从 API 加载工作流配置，工作流ID: {self.workflow_id}")
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# 调用 get_workflow_by_id 获取工作流配置
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response = get_workflow_by_id(self.workflow_id)
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logger.debug(f"API 响应原始数据: {json.dumps(response, ensure_ascii=False, indent=2)}")
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# 返回格式: {code, data, msg}
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if response.get("code") != 200:
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logger.error(f"获取工作流配置失败: code={response.get('code')}, msg={response.get('msg')}")
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return []
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data = response.get("data")
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logger.debug(f"API 响应 data 字段: {json.dumps(data, ensure_ascii=False, indent=2) if data else 'None'}")
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# data 可能是单个对象或列表
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|
if isinstance(data, dict):
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result = [data]
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|
elif isinstance(data, list):
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|
result = data
|
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|
else:
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|
logger.warning(f"API 响应 data 字段类型异常: {type(data)}")
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|
result = []
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|
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||||||
|
logger.info(f"从 API 加载工作流配置成功，工作流ID: {self.workflow_id}, 配置数量: {len(result)}")
|
||||||
|
return result
|
||||||
|
|
||||||
|
except Exception as e:
|
||||||
|
logger.error(f"API 请求失败: {e}", exc_info=True)
|
||||||
|
return []
|
||||||
|
|
||||||
|
|
||||||
|
def create_loader(mode: str, **kwargs) -> DataLoader:
|
||||||
|
"""
|
||||||
|
创建数据加载器
|
||||||
|
|
||||||
|
Args:
|
||||||
|
mode: "local" 或 "api"
|
||||||
|
kwargs:
|
||||||
|
- json_path: 本地 JSON 路径 (local 模式)
|
||||||
|
- workflow_id: 工作流ID (api 模式，可选，默认从环境变量获取)
|
||||||
|
"""
|
||||||
|
if mode == "local":
|
||||||
|
return LocalLoader(json_path=kwargs.get("json_path"))
|
||||||
|
elif mode == "api":
|
||||||
|
return ApiLoader(workflow_id=kwargs.get("workflow_id"))
|
||||||
|
else:
|
||||||
|
raise ValueError(f"不支持的模式: {mode}")
|
||||||
|
|
||||||
|
|
||||||
|
def init_tools(loader: DataLoader):
|
||||||
|
"""初始化工具配置"""
|
||||||
|
global _tools_config
|
||||||
|
_tools_config = loader.load()
|
||||||
|
logger.info(f"已加载 {len(_tools_config)} 个工具配置")
|
||||||
|
|
||||||
|
|
||||||
|
@server.list_tools()
|
||||||
|
async def handle_list_tools() -> list[types.Tool]:
|
||||||
|
"""列出所有可用工具"""
|
||||||
|
logger.info(f"收到 ListTools 请求，当前配置数量: {len(_tools_config)}")
|
||||||
|
tools = []
|
||||||
|
|
||||||
|
for query in _tools_config:
|
||||||
|
name = query.get("name", "")
|
||||||
|
description = query.get("description") or query.get("toolPrompt") or query.get("uniqueName", "")
|
||||||
|
sql_params = query.get("sqlParams", "[]")
|
||||||
|
|
||||||
|
logger.debug(f"处理工具配置: name={name}, description={description[:50] if description else 'None'}...")
|
||||||
|
|
||||||
|
# 转换参数为 inputSchema
|
||||||
|
input_schema = convert_sql_params_to_input_schema(sql_params)
|
||||||
|
logger.debug(f"工具 {name} 的 inputSchema: {json.dumps(input_schema, ensure_ascii=False)}")
|
||||||
|
|
||||||
|
tools.append(
|
||||||
|
types.Tool(
|
||||||
|
name=name,
|
||||||
|
description=description,
|
||||||
|
inputSchema=input_schema
|
||||||
|
)
|
||||||
|
)
|
||||||
|
|
||||||
|
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}, arguments={json.dumps(arguments, ensure_ascii=False) if arguments else 'None'}")
|
||||||
|
|
||||||
|
# 查找对应的工具配置
|
||||||
|
tool_config = None
|
||||||
|
for query in _tools_config:
|
||||||
|
if query.get("name") == name:
|
||||||
|
tool_config = query
|
||||||
|
break
|
||||||
|
|
||||||
|
if tool_config is None:
|
||||||
|
logger.error(f"未找到工具配置: {name}")
|
||||||
|
raise ValueError(f"未知工具: {name}")
|
||||||
|
|
||||||
|
logger.debug(f"找到工具配置: {json.dumps(tool_config, ensure_ascii=False, indent=2)}")
|
||||||
|
|
||||||
|
# 获取工作流ID
|
||||||
|
workflow_id = tool_config.get("workflowId") or get_workflow_id()
|
||||||
|
logger.info(f"使用工作流ID: {workflow_id}")
|
||||||
|
|
||||||
|
# 构建请求数据
|
||||||
|
request_data = {
|
||||||
|
"workflowId": workflow_id,
|
||||||
|
"inputs": arguments or {}
|
||||||
|
}
|
||||||
|
|
||||||
|
logger.info(f"执行工作流请求数据: {json.dumps(request_data, ensure_ascii=False, indent=2)}")
|
||||||
|
|
||||||
|
try:
|
||||||
|
# 调用工作流执行API
|
||||||
|
result = execute_workflow(request_data)
|
||||||
|
logger.info(f"工作流执行成功: {workflow_id}")
|
||||||
|
logger.debug(f"工作流执行结果: {json.dumps(result, ensure_ascii=False, indent=2)}")
|
||||||
|
except Exception as e:
|
||||||
|
logger.error(f"工作流执行失败: {e}", exc_info=True)
|
||||||
|
result = {
|
||||||
|
"error": str(e),
|
||||||
|
"tool_name": name,
|
||||||
|
"workflow_id": workflow_id
|
||||||
|
}
|
||||||
|
|
||||||
|
return [
|
||||||
|
types.TextContent(
|
||||||
|
type="text",
|
||||||
|
text=json.dumps(result, 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="workflow_mcp_server",
|
||||||
|
server_version="0.1.0",
|
||||||
|
capabilities=server.get_capabilities(
|
||||||
|
notification_options=NotificationOptions(),
|
||||||
|
experimental_capabilities={},
|
||||||
|
),
|
||||||
|
),
|
||||||
|
)
|
||||||
|
|
||||||
|
|
||||||
|
def main():
|
||||||
|
"""主入口"""
|
||||||
|
global _config
|
||||||
|
|
||||||
|
logger.info("=" * 50)
|
||||||
|
logger.info("Workflow MCP Server 启动")
|
||||||
|
logger.info("=" * 50)
|
||||||
|
|
||||||
|
# 解析命令行参数
|
||||||
|
args = parse_arguments()
|
||||||
|
_config = vars(args)
|
||||||
|
logger.info(f"命令行参数: {_config}")
|
||||||
|
|
||||||
|
# 创建加载器并初始化工具
|
||||||
|
logger.info(f"使用模式: {args.mode}")
|
||||||
|
loader = create_loader(
|
||||||
|
mode=args.mode,
|
||||||
|
json_path=args.json_path,
|
||||||
|
workflow_id=args.workflow_id
|
||||||
|
)
|
||||||
|
init_tools(loader)
|
||||||
|
|
||||||
|
logger.info("开始运行 MCP Server (stdio 模式)")
|
||||||
|
# 运行服务器
|
||||||
|
anyio.run(run_server)
|
||||||
|
|
||||||
|
|
||||||
|
if __name__ == "__main__":
|
||||||
|
main()
|
||||||
18
lzwcai_workflow_to_mcp/lzwcai_workflow_to_mcp/pyproject.toml
Normal file
18
lzwcai_workflow_to_mcp/lzwcai_workflow_to_mcp/pyproject.toml
Normal file
@@ -0,0 +1,18 @@
|
|||||||
|
[project]
|
||||||
|
name = "lzwcai-workflow-to-mcp"
|
||||||
|
version = "0.1.0"
|
||||||
|
description = "从 businessQueries 动态生成 MCP 工具"
|
||||||
|
readme = "README.md"
|
||||||
|
requires-python = ">=3.10"
|
||||||
|
dependencies = [
|
||||||
|
"mcp>=1.0.0",
|
||||||
|
"anyio>=4.0.0",
|
||||||
|
"requests>=2.28.0",
|
||||||
|
]
|
||||||
|
|
||||||
|
[project.scripts]
|
||||||
|
workflow-mcp = "main:main"
|
||||||
|
|
||||||
|
[build-system]
|
||||||
|
requires = ["hatchling"]
|
||||||
|
build-backend = "hatchling.build"
|
||||||
@@ -0,0 +1,208 @@
|
|||||||
|
"""
|
||||||
|
Schema 转换器
|
||||||
|
将 sqlParams 数组格式转换为 MCP 工具需要的 JSON Schema 格式
|
||||||
|
|
||||||
|
支持的类型:
|
||||||
|
- string: 文本输入
|
||||||
|
- paragraph: 段落/多行文本
|
||||||
|
- select: 下拉选项
|
||||||
|
- number: 数字输入
|
||||||
|
"""
|
||||||
|
import json
|
||||||
|
from typing import Any
|
||||||
|
|
||||||
|
|
||||||
|
def convert_param_to_schema_property(param: dict) -> tuple[str, dict, bool]:
|
||||||
|
"""
|
||||||
|
将单个参数转换为 JSON Schema property
|
||||||
|
|
||||||
|
Args:
|
||||||
|
param: 参数配置，格式如:
|
||||||
|
{
|
||||||
|
"type": "string",
|
||||||
|
"name": "company_names",
|
||||||
|
"displayName": "公司名称",
|
||||||
|
"maxLength": 200,
|
||||||
|
"defaultValue": "",
|
||||||
|
"required": true,
|
||||||
|
"options": ["选项1", "选项2"] # 仅 select 类型
|
||||||
|
}
|
||||||
|
|
||||||
|
Returns:
|
||||||
|
tuple: (property_name, property_schema, is_required)
|
||||||
|
"""
|
||||||
|
param_type = param.get("type", "string")
|
||||||
|
param_name = param.get("name", "")
|
||||||
|
display_name = param.get("displayName", param_name)
|
||||||
|
default_value = param.get("defaultValue", "")
|
||||||
|
max_length = param.get("maxLength")
|
||||||
|
is_required = param.get("required", False)
|
||||||
|
options = param.get("options", [])
|
||||||
|
|
||||||
|
property_schema = {
|
||||||
|
"description": display_name
|
||||||
|
}
|
||||||
|
|
||||||
|
if param_type == "string":
|
||||||
|
property_schema["type"] = "string"
|
||||||
|
if max_length:
|
||||||
|
property_schema["maxLength"] = max_length
|
||||||
|
|
||||||
|
elif param_type == "paragraph":
|
||||||
|
property_schema["type"] = "string"
|
||||||
|
property_schema["format"] = "paragraph"
|
||||||
|
if max_length:
|
||||||
|
property_schema["maxLength"] = max_length
|
||||||
|
|
||||||
|
elif param_type == "select":
|
||||||
|
property_schema["type"] = "string"
|
||||||
|
if options:
|
||||||
|
property_schema["enum"] = options
|
||||||
|
|
||||||
|
elif param_type == "number":
|
||||||
|
property_schema["type"] = "number"
|
||||||
|
|
||||||
|
else:
|
||||||
|
# 默认当作 string 处理
|
||||||
|
property_schema["type"] = "string"
|
||||||
|
|
||||||
|
# 添加默认值
|
||||||
|
if default_value not in (None, ""):
|
||||||
|
if param_type == "number":
|
||||||
|
try:
|
||||||
|
property_schema["default"] = int(default_value) if str(default_value).isdigit() else float(default_value)
|
||||||
|
except (ValueError, TypeError):
|
||||||
|
property_schema["default"] = default_value
|
||||||
|
else:
|
||||||
|
property_schema["default"] = default_value
|
||||||
|
|
||||||
|
return param_name, property_schema, is_required
|
||||||
|
|
||||||
|
|
||||||
|
def convert_sql_params_to_input_schema(sql_params: str | list) -> dict:
|
||||||
|
"""
|
||||||
|
将 sqlParams 转换为 MCP 工具的 inputSchema
|
||||||
|
|
||||||
|
Args:
|
||||||
|
sql_params: sqlParams 字段值，可以是 JSON 字符串或已解析的列表
|
||||||
|
格式: [{"type": "string", "name": "xxx", ...}, ...]
|
||||||
|
|
||||||
|
Returns:
|
||||||
|
dict: MCP 工具的 inputSchema，格式如:
|
||||||
|
{
|
||||||
|
"type": "object",
|
||||||
|
"properties": {...},
|
||||||
|
"required": [...]
|
||||||
|
}
|
||||||
|
"""
|
||||||
|
# 解析 JSON 字符串
|
||||||
|
if isinstance(sql_params, str):
|
||||||
|
try:
|
||||||
|
params_list = json.loads(sql_params)
|
||||||
|
except json.JSONDecodeError:
|
||||||
|
return {"type": "object", "properties": {}, "required": []}
|
||||||
|
else:
|
||||||
|
params_list = sql_params
|
||||||
|
|
||||||
|
if not isinstance(params_list, list):
|
||||||
|
return {"type": "object", "properties": {}, "required": []}
|
||||||
|
|
||||||
|
input_schema = {
|
||||||
|
"type": "object",
|
||||||
|
"properties": {},
|
||||||
|
"required": []
|
||||||
|
}
|
||||||
|
|
||||||
|
for param in params_list:
|
||||||
|
if not isinstance(param, dict):
|
||||||
|
continue
|
||||||
|
|
||||||
|
name, schema, is_required = convert_param_to_schema_property(param)
|
||||||
|
|
||||||
|
if name:
|
||||||
|
input_schema["properties"][name] = schema
|
||||||
|
if is_required:
|
||||||
|
input_schema["required"].append(name)
|
||||||
|
|
||||||
|
return input_schema
|
||||||
|
|
||||||
|
|
||||||
|
def convert_business_query_to_tool(query: dict) -> dict:
|
||||||
|
"""
|
||||||
|
将单个 businessQuery 转换为 MCP Tool 配置
|
||||||
|
|
||||||
|
Args:
|
||||||
|
query: businessQuery 对象
|
||||||
|
|
||||||
|
Returns:
|
||||||
|
dict: MCP Tool 配置
|
||||||
|
{
|
||||||
|
"name": "工具名称",
|
||||||
|
"description": "工具描述",
|
||||||
|
"inputSchema": {...}
|
||||||
|
}
|
||||||
|
"""
|
||||||
|
name = query.get("name", "")
|
||||||
|
description = query.get("description") or query.get("toolPrompt") or query.get("uniqueName", "")
|
||||||
|
sql_params = query.get("sqlParams", "[]")
|
||||||
|
|
||||||
|
input_schema = convert_sql_params_to_input_schema(sql_params)
|
||||||
|
|
||||||
|
return {
|
||||||
|
"name": name,
|
||||||
|
"description": description,
|
||||||
|
"inputSchema": input_schema,
|
||||||
|
# 保留原始数据供后续使用
|
||||||
|
"_raw": {
|
||||||
|
"id": query.get("id"),
|
||||||
|
"uniqueName": query.get("uniqueName"),
|
||||||
|
"sqlTemplate": query.get("sqlTemplate"),
|
||||||
|
"datasourceId": query.get("datasourceId"),
|
||||||
|
"toolType": query.get("toolType"),
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
|
|
||||||
|
def convert_all_queries_to_tools(queries: list[dict]) -> list[dict]:
|
||||||
|
"""
|
||||||
|
将所有 businessQueries 转换为 MCP Tools 列表
|
||||||
|
|
||||||
|
Args:
|
||||||
|
queries: businessQueries 列表
|
||||||
|
|
||||||
|
Returns:
|
||||||
|
list: MCP Tools 配置列表
|
||||||
|
"""
|
||||||
|
tools = []
|
||||||
|
for query in queries:
|
||||||
|
tool = convert_business_query_to_tool(query)
|
||||||
|
if tool["name"]:
|
||||||
|
tools.append(tool)
|
||||||
|
return tools
|
||||||
|
|
||||||
|
|
||||||
|
# 测试用
|
||||||
|
if __name__ == "__main__":
|
||||||
|
# 测试单个参数转换
|
||||||
|
test_param = {
|
||||||
|
"type": "select",
|
||||||
|
"name": "subject_name",
|
||||||
|
"displayName": "科目名称",
|
||||||
|
"maxLength": 100,
|
||||||
|
"defaultValue": "",
|
||||||
|
"required": True,
|
||||||
|
"options": ["管理费用", "销售费用", "财务费用"]
|
||||||
|
}
|
||||||
|
|
||||||
|
name, schema, required = convert_param_to_schema_property(test_param)
|
||||||
|
print(f"参数名: {name}")
|
||||||
|
print(f"Schema: {json.dumps(schema, ensure_ascii=False, indent=2)}")
|
||||||
|
print(f"必填: {required}")
|
||||||
|
print()
|
||||||
|
|
||||||
|
# 测试完整 sqlParams 转换
|
||||||
|
test_sql_params = '[{"type":"paragraph","name":"digest","displayName":"摘要关键字","maxLength":500,"defaultValue":"","required":true},{"type":"string","name":"company_names","displayName":"公司名称","maxLength":200,"defaultValue":"","required":false},{"type":"number","name":"year","displayName":"会计年度","maxLength":4,"defaultValue":"2025","required":true}]'
|
||||||
|
|
||||||
|
input_schema = convert_sql_params_to_input_schema(test_sql_params)
|
||||||
|
print("InputSchema:")
|
||||||
|
print(json.dumps(input_schema, ensure_ascii=False, indent=2))
|
||||||
@@ -0,0 +1,33 @@
|
|||||||
|
"""Utils package for lzwcai_workflow_to_mcp"""
|
||||||
|
|
||||||
|
from .json_helper import load_json
|
||||||
|
from .name_helper import generate_tool_name
|
||||||
|
from .schema_helper import generate_input_schema, validate_input_schema
|
||||||
|
from .api_client import (
|
||||||
|
WorkflowAPIClient,
|
||||||
|
get_workflow_by_id,
|
||||||
|
execute_workflow,
|
||||||
|
process_workflow_response,
|
||||||
|
get_default_client,
|
||||||
|
DEFAULT_TIMEOUT,
|
||||||
|
WORKFLOW_EXECUTE_TIMEOUT
|
||||||
|
)
|
||||||
|
from .env_config import get_workflow_id, get_backend_base_url, get_env_config, set_env_variable
|
||||||
|
|
||||||
|
__all__ = [
|
||||||
|
'load_json',
|
||||||
|
'generate_tool_name',
|
||||||
|
'generate_input_schema',
|
||||||
|
'validate_input_schema',
|
||||||
|
'WorkflowAPIClient',
|
||||||
|
'get_workflow_by_id',
|
||||||
|
'execute_workflow',
|
||||||
|
'process_workflow_response',
|
||||||
|
'get_default_client',
|
||||||
|
'DEFAULT_TIMEOUT',
|
||||||
|
'WORKFLOW_EXECUTE_TIMEOUT',
|
||||||
|
'get_workflow_id',
|
||||||
|
'get_backend_base_url',
|
||||||
|
'get_env_config',
|
||||||
|
'set_env_variable'
|
||||||
|
]
|
||||||
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@@ -0,0 +1,307 @@
|
|||||||
|
"""
|
||||||
|
工作流API调用客户端
|
||||||
|
用于调用工作流管理和执行接口
|
||||||
|
"""
|
||||||
|
|
||||||
|
import httpx
|
||||||
|
import json
|
||||||
|
from typing import Dict, Any, Optional, List
|
||||||
|
|
||||||
|
try:
|
||||||
|
from .env_config import get_backend_base_url, get_workflow_execute_key
|
||||||
|
from .logger_config import get_logger
|
||||||
|
except ImportError:
|
||||||
|
from env_config import get_backend_base_url, get_workflow_execute_key
|
||||||
|
from logger_config import get_logger
|
||||||
|
|
||||||
|
logger = get_logger(__name__)
|
||||||
|
|
||||||
|
# 默认超时配置（秒）
|
||||||
|
DEFAULT_TIMEOUT = 30.0 # 普通请求超时
|
||||||
|
WORKFLOW_EXECUTE_TIMEOUT = 300.0 # 工作流执行超时（5分钟）
|
||||||
|
|
||||||
|
|
||||||
|
class WorkflowAPIClient:
|
||||||
|
"""工作流API客户端"""
|
||||||
|
|
||||||
|
def __init__(
|
||||||
|
self,
|
||||||
|
base_url: Optional[str] = None,
|
||||||
|
token: Optional[str] = None,
|
||||||
|
default_timeout: float = DEFAULT_TIMEOUT,
|
||||||
|
execute_timeout: float = WORKFLOW_EXECUTE_TIMEOUT
|
||||||
|
):
|
||||||
|
"""
|
||||||
|
初始化API客户端
|
||||||
|
|
||||||
|
Args:
|
||||||
|
base_url: API基础URL（默认从环境变量 backendBaseUrl 读取）
|
||||||
|
token: 认证令牌（默认从环境变量 workflowExecuteKey 读取）
|
||||||
|
default_timeout: 普通请求超时时间（秒），默认30秒
|
||||||
|
execute_timeout: 工作流执行超时时间（秒），默认300秒（5分钟）
|
||||||
|
"""
|
||||||
|
if base_url is None:
|
||||||
|
base_url = get_backend_base_url()
|
||||||
|
|
||||||
|
if token is None:
|
||||||
|
token = get_workflow_execute_key()
|
||||||
|
|
||||||
|
self.base_url = base_url.rstrip('/')
|
||||||
|
self.token = token
|
||||||
|
self.default_timeout = default_timeout
|
||||||
|
self.execute_timeout = execute_timeout
|
||||||
|
self._client: Optional[httpx.Client] = None
|
||||||
|
|
||||||
|
logger.debug(f"WorkflowAPIClient 初始化: base_url={self.base_url}, token={'*' * 10 if self.token else 'None'}, execute_timeout={self.execute_timeout}s")
|
||||||
|
|
||||||
|
@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) -> Dict[str, str]:
|
||||||
|
"""获取请求头"""
|
||||||
|
return {
|
||||||
|
'X-API-Key': f'Bearer {self.token}',
|
||||||
|
}
|
||||||
|
|
||||||
|
def get_workflow_by_id(self, workflow_id: str) -> Dict[str, Any]:
|
||||||
|
"""
|
||||||
|
根据工作流ID获取工作流信息
|
||||||
|
|
||||||
|
Args:
|
||||||
|
workflow_id: 工作流ID
|
||||||
|
|
||||||
|
Returns:
|
||||||
|
API响应数据
|
||||||
|
|
||||||
|
Raises:
|
||||||
|
Exception: 请求失败时抛出
|
||||||
|
"""
|
||||||
|
url = f"{self.base_url}/system/workflowManage/getByWorkflowId/{workflow_id}"
|
||||||
|
|
||||||
|
try:
|
||||||
|
logger.info(f"[API请求] GET {url}")
|
||||||
|
logger.debug(f"[API请求] Headers: {self._get_headers()}")
|
||||||
|
|
||||||
|
response = self.client.get(
|
||||||
|
url,
|
||||||
|
headers=self._get_headers()
|
||||||
|
)
|
||||||
|
|
||||||
|
logger.info(f"[API响应] HTTP {response.status_code}")
|
||||||
|
logger.debug(f"[API响应] Headers: {dict(response.headers)}")
|
||||||
|
|
||||||
|
response.raise_for_status()
|
||||||
|
data = response.json()
|
||||||
|
|
||||||
|
logger.info(f"[API响应] 获取工作流配置成功: workflow_id={workflow_id}")
|
||||||
|
logger.debug(f"[API响应] Body: {json.dumps(data, ensure_ascii=False, indent=2)}")
|
||||||
|
|
||||||
|
return data
|
||||||
|
|
||||||
|
except httpx.TimeoutException:
|
||||||
|
error_msg = f"API请求超时: {url}"
|
||||||
|
logger.error(f"[API错误] {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}"
|
||||||
|
logger.error(f"[API错误] {error_msg}")
|
||||||
|
logger.error(f"[API错误] 响应内容: {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)}"
|
||||||
|
logger.error(f"[API错误] {error_msg}")
|
||||||
|
raise Exception(error_msg)
|
||||||
|
|
||||||
|
except Exception as e:
|
||||||
|
error_msg = f"处理API响应时出错: {str(e)}"
|
||||||
|
logger.error(f"[API错误] {error_msg}", exc_info=True)
|
||||||
|
raise Exception(error_msg)
|
||||||
|
|
||||||
|
def execute_workflow(self, request_data: Dict[str, Any]) -> Dict[str, Any]:
|
||||||
|
"""
|
||||||
|
执行工作流
|
||||||
|
|
||||||
|
Args:
|
||||||
|
request_data: 请求数据，包含工作流执行所需的参数
|
||||||
|
|
||||||
|
Returns:
|
||||||
|
API响应数据
|
||||||
|
|
||||||
|
Raises:
|
||||||
|
Exception: 请求失败时抛出
|
||||||
|
"""
|
||||||
|
url = f"{self.base_url}/open/workflow/execute"
|
||||||
|
|
||||||
|
try:
|
||||||
|
headers = self._get_headers()
|
||||||
|
headers['Content-Type'] = 'application/json'
|
||||||
|
headers['Accept'] = '*/*'
|
||||||
|
|
||||||
|
logger.info(f"[API请求] POST {url} (超时: {self.execute_timeout}s)")
|
||||||
|
logger.debug(f"[API请求] Headers: {headers}")
|
||||||
|
logger.debug(f"[API请求] Body: {json.dumps(request_data, ensure_ascii=False, indent=2)}")
|
||||||
|
|
||||||
|
# 使用更长的超时时间执行工作流
|
||||||
|
response = self.client.post(
|
||||||
|
url,
|
||||||
|
headers=headers,
|
||||||
|
json=request_data,
|
||||||
|
timeout=self.execute_timeout # 使用工作流执行专用超时时间
|
||||||
|
)
|
||||||
|
|
||||||
|
logger.info(f"[API响应] HTTP {response.status_code}")
|
||||||
|
logger.debug(f"[API响应] Headers: {dict(response.headers)}")
|
||||||
|
|
||||||
|
response.raise_for_status()
|
||||||
|
data = response.json()
|
||||||
|
|
||||||
|
logger.info(f"[API响应] 执行工作流成功")
|
||||||
|
logger.debug(f"[API响应] Body: {json.dumps(data, ensure_ascii=False, indent=2)}")
|
||||||
|
|
||||||
|
return data
|
||||||
|
|
||||||
|
except httpx.TimeoutException:
|
||||||
|
error_msg = f"执行工作流API请求超时: {url}"
|
||||||
|
logger.error(f"[API错误] {error_msg}")
|
||||||
|
raise Exception(error_msg)
|
||||||
|
|
||||||
|
except httpx.HTTPStatusError as e:
|
||||||
|
error_msg = f"执行工作流API请求失败 (HTTP {e.response.status_code}): {url}"
|
||||||
|
logger.error(f"[API错误] {error_msg}")
|
||||||
|
logger.error(f"[API错误] 响应内容: {e.response.text}")
|
||||||
|
raise Exception(error_msg)
|
||||||
|
|
||||||
|
except httpx.RequestError as e:
|
||||||
|
error_msg = f"执行工作流API请求异常: {url}, 错误: {str(e)}"
|
||||||
|
logger.error(f"[API错误] {error_msg}")
|
||||||
|
raise Exception(error_msg)
|
||||||
|
|
||||||
|
except Exception as e:
|
||||||
|
error_msg = f"处理执行工作流API响应时出错: {str(e)}"
|
||||||
|
logger.error(f"[API错误] {error_msg}", exc_info=True)
|
||||||
|
raise Exception(error_msg)
|
||||||
|
|
||||||
|
def close(self):
|
||||||
|
"""关闭HTTP客户端"""
|
||||||
|
if self._client is not None:
|
||||||
|
self._client.close()
|
||||||
|
self._client = None
|
||||||
|
|
||||||
|
def __enter__(self):
|
||||||
|
"""支持 context manager"""
|
||||||
|
return self
|
||||||
|
|
||||||
|
def __exit__(self, exc_type, exc_val, exc_tb):
|
||||||
|
"""退出时关闭客户端"""
|
||||||
|
self.close()
|
||||||
|
return False
|
||||||
|
|
||||||
|
|
||||||
|
# 懒加载的默认客户端
|
||||||
|
_default_client: Optional[WorkflowAPIClient] = None
|
||||||
|
|
||||||
|
|
||||||
|
def get_default_client() -> WorkflowAPIClient:
|
||||||
|
"""获取默认客户端（懒加载）"""
|
||||||
|
global _default_client
|
||||||
|
if _default_client is None:
|
||||||
|
_default_client = WorkflowAPIClient()
|
||||||
|
return _default_client
|
||||||
|
|
||||||
|
|
||||||
|
def get_workflow_by_id(workflow_id: str, base_url: Optional[str] = None, token: Optional[str] = None) -> Dict[str, Any]:
|
||||||
|
"""
|
||||||
|
便捷函数：根据工作流ID获取工作流信息
|
||||||
|
|
||||||
|
Args:
|
||||||
|
workflow_id: 工作流ID
|
||||||
|
base_url: API基础URL（可选）
|
||||||
|
token: 认证令牌（可选）
|
||||||
|
|
||||||
|
Returns:
|
||||||
|
API响应数据
|
||||||
|
"""
|
||||||
|
if base_url or token:
|
||||||
|
with WorkflowAPIClient(base_url=base_url, token=token) as client:
|
||||||
|
return client.get_workflow_by_id(workflow_id)
|
||||||
|
else:
|
||||||
|
return get_default_client().get_workflow_by_id(workflow_id)
|
||||||
|
|
||||||
|
|
||||||
|
def execute_workflow(
|
||||||
|
request_data: Dict[str, Any],
|
||||||
|
base_url: Optional[str] = None,
|
||||||
|
token: Optional[str] = None,
|
||||||
|
timeout: float = WORKFLOW_EXECUTE_TIMEOUT
|
||||||
|
) -> Dict[str, Any]:
|
||||||
|
"""
|
||||||
|
便捷函数：执行工作流
|
||||||
|
|
||||||
|
Args:
|
||||||
|
request_data: 请求数据
|
||||||
|
base_url: API基础URL（可选）
|
||||||
|
token: 认证令牌（可选）
|
||||||
|
timeout: 超时时间（秒），默认300秒（5分钟）
|
||||||
|
|
||||||
|
Returns:
|
||||||
|
API响应数据
|
||||||
|
"""
|
||||||
|
if base_url or token:
|
||||||
|
with WorkflowAPIClient(base_url=base_url, token=token, execute_timeout=timeout) as client:
|
||||||
|
return client.execute_workflow(request_data)
|
||||||
|
else:
|
||||||
|
# 更新默认客户端的超时时间
|
||||||
|
default_client = get_default_client()
|
||||||
|
default_client.execute_timeout = timeout
|
||||||
|
return default_client.execute_workflow(request_data)
|
||||||
|
|
||||||
|
|
||||||
|
def process_workflow_response(response: Dict[str, Any]) -> List[Dict[str, Any]]:
|
||||||
|
"""
|
||||||
|
处理API响应数据，映射为工作流配置格式
|
||||||
|
|
||||||
|
Args:
|
||||||
|
response: API原始响应数据
|
||||||
|
|
||||||
|
Returns:
|
||||||
|
处理后的工作流配置列表
|
||||||
|
"""
|
||||||
|
try:
|
||||||
|
data_list = response.get("data", [])
|
||||||
|
|
||||||
|
# 如果 data 是单个对象而不是列表，转换为列表
|
||||||
|
if isinstance(data_list, dict):
|
||||||
|
data_list = [data_list]
|
||||||
|
|
||||||
|
workflows = []
|
||||||
|
for workflow in data_list:
|
||||||
|
# 解析 inputParams 字符串为 JSON 对象
|
||||||
|
input_params = workflow.get("inputParams", {})
|
||||||
|
if isinstance(input_params, str):
|
||||||
|
try:
|
||||||
|
input_params = json.loads(input_params)
|
||||||
|
except json.JSONDecodeError:
|
||||||
|
input_params = {}
|
||||||
|
|
||||||
|
# 映射字段
|
||||||
|
config = {
|
||||||
|
"id": workflow.get("id"),
|
||||||
|
"workflowId": workflow.get("workflowId"),
|
||||||
|
"workflowName": workflow.get("workflowName") or workflow.get("name"),
|
||||||
|
"workflowDescription": workflow.get("workflowDescription") or workflow.get("description"),
|
||||||
|
"inputParams": input_params
|
||||||
|
}
|
||||||
|
workflows.append(config)
|
||||||
|
|
||||||
|
logger.info(f"成功处理 {len(workflows)} 条工作流数据")
|
||||||
|
return workflows
|
||||||
|
|
||||||
|
except Exception as e:
|
||||||
|
logger.error(f"处理API响应数据失败: {e}", exc_info=True)
|
||||||
|
raise
|
||||||
@@ -0,0 +1,85 @@
|
|||||||
|
"""环境变量配置模块"""
|
||||||
|
|
||||||
|
import os
|
||||||
|
from typing import Optional
|
||||||
|
|
||||||
|
|
||||||
|
def get_workflow_id(default: str = "") -> str:
|
||||||
|
"""
|
||||||
|
获取工作流ID环境变量
|
||||||
|
|
||||||
|
Args:
|
||||||
|
default: 默认值（默认为 ""）
|
||||||
|
|
||||||
|
Returns:
|
||||||
|
str: 工作流ID
|
||||||
|
|
||||||
|
Environment Variables:
|
||||||
|
workflowId: 工作流ID
|
||||||
|
"""
|
||||||
|
return os.environ.get("workflowId", default)
|
||||||
|
|
||||||
|
|
||||||
|
def get_backend_base_url(default: str = "http://lzwcai-demp-corp-manager:8086") -> str:
|
||||||
|
"""
|
||||||
|
获取后端API基础URL环境变量
|
||||||
|
|
||||||
|
Args:
|
||||||
|
default: 默认值（默认为 "http://lzwcai-demp-corp-manager:8086"）
|
||||||
|
|
||||||
|
Returns:
|
||||||
|
str: 后端API基础URL
|
||||||
|
|
||||||
|
Environment Variables:
|
||||||
|
backendBaseUrl: 后端API基础URL
|
||||||
|
"""
|
||||||
|
return os.environ.get("backendBaseUrl", default)
|
||||||
|
|
||||||
|
|
||||||
|
def get_workflow_execute_key(default: str = "") -> str:
|
||||||
|
"""
|
||||||
|
获取工作流执行密钥（Token）环境变量
|
||||||
|
|
||||||
|
Args:
|
||||||
|
default: 默认值（默认为 ""）
|
||||||
|
|
||||||
|
Returns:
|
||||||
|
str: 工作流执行密钥
|
||||||
|
|
||||||
|
Environment Variables:
|
||||||
|
workflowExecuteKey: 工作流执行密钥/Token
|
||||||
|
"""
|
||||||
|
return os.environ.get("workflowExecuteKey", 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
|
||||||
|
|
||||||
|
Example:
|
||||||
|
config = get_env_config()
|
||||||
|
print(config['workflow_id']) # 输出: ""
|
||||||
|
print(config['backend_base_url']) # 输出: "http://lzwcai-demp-corp-manager:8086"
|
||||||
|
"""
|
||||||
|
return {
|
||||||
|
"workflow_id": get_workflow_id(),
|
||||||
|
"backend_base_url": get_backend_base_url(),
|
||||||
|
"workflow_execute_key": get_workflow_execute_key()
|
||||||
|
}
|
||||||
|
|
||||||
|
|
||||||
|
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
|
||||||
|
|
||||||
|
Example:
|
||||||
|
set_env_variable("workflowId", "1234567890")
|
||||||
|
"""
|
||||||
|
os.environ[key] = value
|
||||||
@@ -0,0 +1,59 @@
|
|||||||
|
"""JSON 文件读取工具"""
|
||||||
|
|
||||||
|
import json
|
||||||
|
from pathlib import Path
|
||||||
|
from typing import Any, Union
|
||||||
|
|
||||||
|
|
||||||
|
def load_json(json_path: Union[str, Path]) -> Any:
|
||||||
|
"""
|
||||||
|
读取 JSON 文件并返回其内容
|
||||||
|
|
||||||
|
Args:
|
||||||
|
json_path: JSON 文件的路径（支持字符串或 Path 对象）
|
||||||
|
|
||||||
|
Returns:
|
||||||
|
JSON 文件中解析后的数据（可以是字典、列表或其他 JSON 类型）
|
||||||
|
|
||||||
|
Raises:
|
||||||
|
FileNotFoundError: 当文件不存在时
|
||||||
|
json.JSONDecodeError: 当 JSON 格式无效时
|
||||||
|
Exception: 其他读取错误
|
||||||
|
|
||||||
|
Example:
|
||||||
|
>>> data = load_json('config.json')
|
||||||
|
>>> print(data)
|
||||||
|
{'key': 'value'}
|
||||||
|
|
||||||
|
>>> data = load_json(Path('data/users.json'))
|
||||||
|
>>> print(data)
|
||||||
|
[{'id': 1, 'name': 'Alice'}]
|
||||||
|
"""
|
||||||
|
try:
|
||||||
|
# 转换为 Path 对象
|
||||||
|
path = Path(json_path)
|
||||||
|
|
||||||
|
# 检查文件是否存在
|
||||||
|
if not path.exists():
|
||||||
|
raise FileNotFoundError(f"JSON 文件不存在: {json_path}")
|
||||||
|
|
||||||
|
# 检查是否为文件
|
||||||
|
if not path.is_file():
|
||||||
|
raise ValueError(f"路径不是一个文件: {json_path}")
|
||||||
|
|
||||||
|
# 读取并解析 JSON 文件
|
||||||
|
with open(path, 'r', encoding='utf-8') as f:
|
||||||
|
data = json.load(f)
|
||||||
|
|
||||||
|
return data
|
||||||
|
|
||||||
|
except json.JSONDecodeError as e:
|
||||||
|
raise json.JSONDecodeError(
|
||||||
|
f"JSON 格式错误: {e.msg}",
|
||||||
|
e.doc,
|
||||||
|
e.pos
|
||||||
|
)
|
||||||
|
except FileNotFoundError:
|
||||||
|
raise
|
||||||
|
except Exception as e:
|
||||||
|
raise Exception(f"读取 JSON 文件时发生错误: {str(e)}")
|
||||||
@@ -0,0 +1,174 @@
|
|||||||
|
# -*- 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, TimedRotatingFileHandler
|
||||||
|
from datetime import datetime
|
||||||
|
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_workflow_to_mcp",
|
||||||
|
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. 按日期滚动的日志文件
|
||||||
|
daily_log_file = self.logs_dir / f"{app_name}_daily.log"
|
||||||
|
daily_handler = TimedRotatingFileHandler(
|
||||||
|
daily_log_file,
|
||||||
|
when='midnight',
|
||||||
|
interval=1,
|
||||||
|
backupCount=30,
|
||||||
|
encoding='utf-8'
|
||||||
|
)
|
||||||
|
daily_handler.setLevel(log_level)
|
||||||
|
daily_handler.setFormatter(formatter)
|
||||||
|
daily_handler.suffix = "%Y-%m-%d"
|
||||||
|
root_logger.addHandler(daily_handler)
|
||||||
|
|
||||||
|
# 4. 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, module_name: str) -> logging.Logger:
|
||||||
|
return logging.getLogger(module_name)
|
||||||
|
|
||||||
|
def create_component_logger(self,
|
||||||
|
component_name: str,
|
||||||
|
log_file: str = None,
|
||||||
|
log_level: int = None) -> logging.Logger:
|
||||||
|
logger = logging.getLogger(component_name)
|
||||||
|
|
||||||
|
if log_file:
|
||||||
|
component_log_file = self.logs_dir / log_file
|
||||||
|
handler = RotatingFileHandler(
|
||||||
|
component_log_file,
|
||||||
|
maxBytes=5 * 1024 * 1024,
|
||||||
|
backupCount=3,
|
||||||
|
encoding='utf-8'
|
||||||
|
)
|
||||||
|
|
||||||
|
formatter = logging.Formatter(self.log_format, self.date_format)
|
||||||
|
handler.setFormatter(formatter)
|
||||||
|
|
||||||
|
if log_level:
|
||||||
|
handler.setLevel(log_level)
|
||||||
|
|
||||||
|
logger.addHandler(handler)
|
||||||
|
|
||||||
|
return logger
|
||||||
|
|
||||||
|
def setup_mcp_logging(self) -> logging.Logger:
|
||||||
|
return self.create_component_logger(
|
||||||
|
"mcp_services",
|
||||||
|
"mcp_services.log",
|
||||||
|
logging.DEBUG
|
||||||
|
)
|
||||||
|
|
||||||
|
def setup_api_logging(self) -> logging.Logger:
|
||||||
|
return self.create_component_logger(
|
||||||
|
"api_requests",
|
||||||
|
"api_requests.log",
|
||||||
|
logging.INFO
|
||||||
|
)
|
||||||
|
|
||||||
|
|
||||||
|
# 全局日志配置实例
|
||||||
|
logger_config = LoggerConfig()
|
||||||
|
|
||||||
|
|
||||||
|
def setup_system_logging(app_name: str = "lzwcai_workflow_to_mcp",
|
||||||
|
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)
|
||||||
@@ -0,0 +1,40 @@
|
|||||||
|
# -*- coding: utf-8 -*-
|
||||||
|
"""
|
||||||
|
名称生成工具模块
|
||||||
|
"""
|
||||||
|
|
||||||
|
from pypinyin import lazy_pinyin, Style
|
||||||
|
import logging
|
||||||
|
|
||||||
|
logger = logging.getLogger(__name__)
|
||||||
|
|
||||||
|
|
||||||
|
def generate_tool_name(business_name: str, tool_id: str) -> str:
|
||||||
|
"""
|
||||||
|
根据业务名称和ID生成工具名称
|
||||||
|
格式: tool_拼音_id
|
||||||
|
|
||||||
|
Args:
|
||||||
|
business_name: 业务名称（中文）
|
||||||
|
tool_id: 工具ID
|
||||||
|
|
||||||
|
Returns:
|
||||||
|
str: 格式化的工具名称
|
||||||
|
"""
|
||||||
|
try:
|
||||||
|
# 将中文转换为拼音（无音调，小写）
|
||||||
|
pinyin_list = lazy_pinyin(business_name, style=Style.NORMAL)
|
||||||
|
# 拼接拼音
|
||||||
|
pinyin_str = ''.join(pinyin_list)
|
||||||
|
|
||||||
|
# 将 ID 中的 '-' 替换为 '_'
|
||||||
|
formatted_id = tool_id.replace('-', '_')
|
||||||
|
|
||||||
|
# 组合成最终的工具名称
|
||||||
|
tool_name = f"workflow_{pinyin_str}_{formatted_id}"
|
||||||
|
|
||||||
|
return tool_name
|
||||||
|
except Exception as e:
|
||||||
|
logger.error(f"生成工具名称失败: {business_name}, {tool_id}, 错误: {e}", exc_info=True)
|
||||||
|
# 降级处理：如果拼音转换失败，使用 ID
|
||||||
|
return f"workflow_{tool_id.replace('-', '_')}"
|
||||||
@@ -0,0 +1,94 @@
|
|||||||
|
# -*- coding: utf-8 -*-
|
||||||
|
"""
|
||||||
|
Schema 生成工具模块
|
||||||
|
"""
|
||||||
|
|
||||||
|
from typing import Any, Dict, List
|
||||||
|
|
||||||
|
|
||||||
|
def generate_input_schema(parameters: Dict[str, Any]) -> Dict[str, Any]:
|
||||||
|
"""
|
||||||
|
从查询配置的参数定义生成 MCP 工具的 inputSchema
|
||||||
|
|
||||||
|
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
|
||||||
|
|
||||||
|
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
|
||||||
|
"""
|
||||||
|
# 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 = dict(parameters)
|
||||||
|
|
||||||
|
# 确保必需的字段存在
|
||||||
|
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:
|
||||||
|
input_schema["required"] = []
|
||||||
|
|
||||||
|
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
|
||||||
|
|
||||||
|
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)
|
||||||
|
"""
|
||||||
|
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"
|
||||||
16
lzwcai_workflow_to_mcp/main.py
Normal file
16
lzwcai_workflow_to_mcp/main.py
Normal file
@@ -0,0 +1,16 @@
|
|||||||
|
"""
|
||||||
|
Entry point for lzwcai-workflow-to-mcp
|
||||||
|
Runs the MCP server for workflow execution
|
||||||
|
"""
|
||||||
|
|
||||||
|
import os
|
||||||
|
|
||||||
|
if __name__ == "__main__":
|
||||||
|
# 设置环境变量
|
||||||
|
os.environ["workflowId"] = "2002300699510763521"
|
||||||
|
os.environ["workflowExecuteKey"] = "wf_buh230o9iaea4n6aefsddcexa7p27ydl"
|
||||||
|
os.environ["backendBaseUrl"] = "http://192.168.2.236:8088"
|
||||||
|
|
||||||
|
# Import and run the actual MCP server
|
||||||
|
from lzwcai_workflow_to_mcp.main import main
|
||||||
|
main()
|
||||||
35
lzwcai_workflow_to_mcp/pyproject.toml
Normal file
35
lzwcai_workflow_to_mcp/pyproject.toml
Normal file
@@ -0,0 +1,35 @@
|
|||||||
|
[build-system]
|
||||||
|
requires = ["hatchling"]
|
||||||
|
build-backend = "hatchling.build"
|
||||||
|
|
||||||
|
[project]
|
||||||
|
name = "lzwcai-workflow-to-mcp"
|
||||||
|
version = "0.1.8"
|
||||||
|
description = "MCP server for executing business SQL queries with dynamic tool generation"
|
||||||
|
readme = "README.md"
|
||||||
|
requires-python = ">=3.13"
|
||||||
|
license = {text = "MIT"}
|
||||||
|
authors = [
|
||||||
|
{name = "lzwcai", email = "your-email@example.com"},
|
||||||
|
]
|
||||||
|
keywords = ["mcp", "sql", "executor", "server"]
|
||||||
|
classifiers = [
|
||||||
|
"Development Status :: 3 - Alpha",
|
||||||
|
"Intended Audience :: Developers",
|
||||||
|
"Programming Language :: Python :: 3",
|
||||||
|
"Programming Language :: Python :: 3.13",
|
||||||
|
]
|
||||||
|
dependencies = [
|
||||||
|
"httpx>=0.28.1",
|
||||||
|
"mcp[cli]>=1.10.1",
|
||||||
|
"pypinyin>=0.53.0",
|
||||||
|
]
|
||||||
|
|
||||||
|
[project.scripts]
|
||||||
|
lzwcai-workflow-to-mcp = "lzwcai_workflow_to_mcp.main:main"
|
||||||
|
|
||||||
|
[tool.hatch.build.targets.wheel]
|
||||||
|
packages = ["lzwcai_workflow_to_mcp"]
|
||||||
|
|
||||||
|
[tool.hatch.build.targets.wheel.force-include]
|
||||||
|
"lzwcai_workflow_to_mcp/businessQueries.json" = "lzwcai_workflow_to_mcp/businessQueries.json"
|
||||||
Reference in New Issue
Block a user