feat(mfg-data-agent): 重构项目为制造业数据智能体

- 将项目从 lzwcai-mcpskills-analyzeOrder 重命名为 lzwcai-mcpskills-mfg-data-agent
- 更新 README.md 中的项目描述，专注制造业数据分析与智能决策
- 修改配置文件和安装命令以匹配新项目名称
- 更新 MCP 服务器配置，使用新的命令名称
- 调整示例查询配置，从用户订单查询改为生产订单查询
- 更新依赖包和模块导入路径
- 修正项目描述和关键词，突出制造业数据智能体特性

lzwcai_mcpskills_mfg_data_agent/README.md

@@ -1,6 +1,6 @@
-# lzwcai-mcpskills-analyzeOrder
+# lzwcai-mcpskills-mfg-data-agent (制造业数据智能体)
 
-一个基于 MCP (Model Context Protocol) 的 SQL 查询执行服务器，支持从 JSON 配置文件动态生成查询工具。
+一个基于 MCP (Model Context Protocol) 的制造业数据智能体服务器，支持从 JSON 配置文件动态生成查询工具。
 
 ## 功能特性
 
@@ -8,27 +8,28 @@
 - 🔧 灵活配置：支持自定义业务查询和参数验证
 - 📝 完整日志：详细的操作日志记录
 - 🌐 中文支持：工具名称自动转换为拼音
+- 🏭 制造业场景：专注于制造业数据分析与智能决策
 
 ## 安装
 
 ### 使用 pip 安装
 
 ```bash
-pip install lzwcai-mcpskills-analyzeOrder
+pip install lzwcai-mcpskills-mfg-data-agent
 ```
 
 ### 从源码安装
 
 ```bash
 git clone <repository-url>
-cd lzwcai_mcp_sqlexecutor
+cd lzwcai_mcpskills_mfg_data_agent
 pip install -e .
 ```
 
 ### 使用 uv 安装（推荐）
 
 ```bash
-uv pip install lzwcai-mcpskills-analyzeOrder
+uv pip install lzwcai-mcpskills-mfg-data-agent
 ```
 
 ## 使用方法
@@ -38,13 +39,13 @@ uv pip install lzwcai-mcpskills-analyzeOrder
 安装后，可以直接通过命令启动：
 
 ```bash
-lzwcai-mcpskills-analyzeOrder
+lzwcai-mcpskills-mfg-data-agent
 ```
 
 ### 作为 Python 模块运行
 
 ```bash
-python -m lzwcai_mcp_sqlexecutor.main
+python -m lzwcai_mcpskills_mfg_data_agent.main
 ```
 
 ### 配置到 MCP 客户端
@@ -54,8 +55,8 @@ python -m lzwcai_mcp_sqlexecutor.main
 ```json
 {
   "mcpServers": {
-    "lzwcai-sqlexecutor": {
+    "mfg-data-agent": {
-      "command": "lzwcai-mcpskills-analyzeOrder"
+      "command": "lzwcai-mcpskills-mfg-data-agent"
     }
   }
 }
@@ -71,17 +72,17 @@ python -m lzwcai_mcp_sqlexecutor.main
 [
   {
     "id": "query-001",
-    "businessName": "用户订单查询",
+    "businessName": "生产订单查询",
-    "businessDescription": "根据用户ID查询订单信息",
+    "businessDescription": "根据订单ID查询生产订单信息",
-    "sqlTemplate": "SELECT * FROM orders WHERE user_id = {{userId}}",
+    "sqlTemplate": "SELECT * FROM production_orders WHERE order_id = {{orderId}}",
     "parameters": {
       "type": "object",
-      "required": ["userId"],
+      "required": ["orderId"],
       "properties": {
-        "userId": {
+        "orderId": {
-          "type": "integer",
+          "type": "string",
-          "description": "用户的唯一标识符",
+          "description": "生产订单的唯一标识符",
-          "examples": [10086]
+          "examples": ["PO-2024-001"]
         }
       }
     }
@@ -103,13 +104,13 @@ python -m lzwcai_mcp_sqlexecutor.main
 ```bash
 # 克隆仓库
 git clone <repository-url>
-cd lzwcai_mcp_sqlexecutor
+cd lzwcai_mcpskills_mfg_data_agent
 
 # 安装开发依赖
 pip install -e .
 
 # 运行服务器
-python -m lzwcai_mcp_sqlexecutor.main
+python -m lzwcai_mcpskills_mfg_data_agent.main
 ```
 
 ## 构建与发布
@@ -135,4 +136,3 @@ MIT License
 ## 作者
 
 lzwcai
-

lzwcai_mcpskills_mfg_data_agent/lzwcai_mcpskills_mfg_data_agent/pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "hatchling.build"
 
 [project]
 name = "lzwcai-mcpskills-analyzeWorkOrder"
-version = "0.1.10"
+version = "0.1.1"
 description = "MCP server for executing business SQL queries with dynamic tool generation"
 readme = "README.md"
 requires-python = ">=3.13"

lzwcai_mcpskills_mfg_data_agent/main.py

@@ -1,6 +1,6 @@
 """
-Entry point for lzwcai-mcpskills-analyzeOrder
+Entry point for lzwcai-mcpskills-mfg-data-agent (制造业数据智能体)
-Runs the MCP server for SQL query execution
+Runs the MCP server for manufacturing data intelligence
 """
 import os
 
@@ -9,5 +9,5 @@ os.environ["datasourceId"] = "19"
 os.environ["backendBaseUrl"] = "http://192.168.11.24:8088"
 if __name__ == "__main__":
     # Import and run the actual MCP server
-    from lzwcai_mcpskills_analyzeOrder.main import main
+    from lzwcai_mcpskills_mfg_data_agent.main import main
     main()

lzwcai_mcpskills_mfg_data_agent/pyproject.toml

@@ -3,16 +3,16 @@ requires = ["hatchling"]
 build-backend = "hatchling.build"
 
 [project]
-name = "lzwcai-mcpskills-analyzeOrder"
+name = "lzwcai-mcpskills-mfg-data-agent"
-version = "0.1.12"
+version = "0.1.1"
-description = "MCP server for executing business SQL queries with dynamic tool generation"
+description = "制造业数据智能体 - MCP server for manufacturing data intelligence 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"]
+keywords = ["mcp", "sql", "manufacturing", "data", "agent", "智能体"]
 classifiers = [
     "Development Status :: 3 - Alpha",
     "Intended Audience :: Developers",
@@ -26,10 +26,10 @@ dependencies = [
 ]
 
 [project.scripts]
-lzwcai-mcpskills-analyzeOrder = "lzwcai_mcpskills_analyzeOrder.main:main"
+lzwcai-mcpskills-mfg-data-agent = "lzwcai_mcpskills_mfg_data_agent.main:main"
 
 [tool.hatch.build.targets.wheel]
-packages = ["lzwcai_mcpskills_analyzeOrder"]
+packages = ["lzwcai_mcpskills_mfg_data_agent"]
 
 [tool.hatch.build.targets.wheel.force-include]
-"lzwcai_mcpskills_analyzeOrder/businessQueries.json" = "lzwcai_mcpskills_analyzeOrder/businessQueries.json"
+"lzwcai_mcpskills_mfg_data_agent/businessQueries.json" = "lzwcai_mcpskills_mfg_data_agent/businessQueries.json"