MCP Client 示例（open ai 实现）

环境准备

# Create project directory
uv init mcp-client
cd mcp-client

# Create virtual environment
uv venv

# Activate virtual environment
# On Windows:
.venv\Scripts\activate

# Install required packages
uv add mcp openai python-dotenv

# Create our main file
echo. >  client.py

.env文件
在这里插入图片描述

client.py 代码

import asyncio
from typing import Optional
from contextlib import AsyncExitStack
import os
import json

from mcp import ClientSession, StdioServerParameters
from mcp.client.stdio import stdio_client

from openai import OpenAI
from dotenv import load_dotenv

load_dotenv()  # load environment variables from .env

api_key = os.environ["OPENAI_API_KEY"]
base_url = os.environ["OPENAI_API_BASE"]


# What are the weather alert in California
class MCPClient:
    def __init__(self):
        # Initialize session and client objects
        self.session: Optional[ClientSession] = None
        self.exit_stack = AsyncExitStack()

        self.openai = OpenAI(api_key=api_key, base_url=base_url)

    async def connect_to_server(self, server_script_path: str):
        """Connect to an MCP server

        Args:
            server_script_path: Path to the server script (.py or .js)
        """
        is_python = server_script_path.endswith(".py")
        is_js = server_script_path.endswith(".js")
        if not (is_python or is_js):
            raise ValueError("Server script must be a .py or .js file")

        command = (
            "D:\\llm\\MCP\\mcp-client\\.venv\\Scripts\\python.exe"
            if is_python
            else "node"
        )
        server_params = StdioServerParameters(
            command=command, args=[server_script_path], env=None
        )

        stdio_transport = await self.exit_stack.enter_async_context(
            stdio_client(server_params)
        )
        self.stdio, self.write = stdio_transport
        self.session = await self.exit_stack.enter_async_context(
            ClientSession(self.stdio, self.write)
        )

        await self.session.initialize()

        # List available tools
        response = await self.session.list_tools()
        tools = response.tools
        print(
            "\nConnected to server with tools:",
            [[tool.name, tool.description, tool.inputSchema] for tool in tools],
        )

    async def process_query(self, query: str) -> str:
        """Process a query using Claude and available tools"""
        messages = [{"role": "user", "content": query}]

        response = await self.session.list_tools()

        available_tools = []

        for tool in response.tools:
            tool_schema = getattr(
                tool,
                "inputSchema",
                {"type": "object", "properties": {}, "required": []},
            )

            openai_tool = {
                "type": "function",
                "function": {
                    "name": tool.name,
                    "description": tool.description,
                    "parameters": tool_schema,
                },
            }
            available_tools.append(openai_tool)

        # Initial Claude API call
        model_response = self.openai.chat.completions.create(
            model="GLM-4-Air-0111",
            max_tokens=1000,
            messages=messages,
            tools=available_tools,
        )

        # Process response and handle tool calls
        tool_results = []
        final_text = []

        messages.append(model_response.choices[0].message.model_dump())
        print(messages[-1])
        if model_response.choices[0].message.tool_calls:
            tool_call = model_response.choices[0].message.tool_calls[0]
            tool_args = json.loads(tool_call.function.arguments)

            tool_name = tool_call.function.name
            result = await self.session.call_tool(tool_name, tool_args)
            tool_results.append({"call": tool_name, "result": result})
            final_text.append(f"[Calling tool {tool_name} with args {tool_args}]")

            messages.append(
                {
                    "role": "tool",
                    "content": f"{result}",
                    "tool_call_id": tool_call.id,
                }
            )

            # Get next response from Claude
            response = self.openai.chat.completions.create(
                model="GLM-4-Air-0111",
                max_tokens=1000,
                messages=messages,
            )

            messages.append(response.choices[0].message.model_dump())
            print(messages[-1])

        return messages[-1]["content"]

    async def chat_loop(self):
        """Run an interactive chat loop"""
        print("\nMCP Client Started!")
        print("Type your queries or 'quit' to exit.")

        while True:
            try:
                query = input("\nQuery: ").strip()

                if query.lower() == "quit":
                    break

                response = await self.process_query(query)
                print("\n" + response)

            except Exception as e:
                print(f"\nError: {str(e)}")

    async def cleanup(self):
        """Clean up resources"""
        await self.exit_stack.aclose()


async def main():
    if len(sys.argv) < 2:
        print("Usage: python client.py <path_to_server_script>")
        sys.exit(1)

    client = MCPClient()
    try:
        await client.connect_to_server(sys.argv[1])
        await client.chat_loop()
    finally:
        await client.cleanup()


if __name__ == "__main__":
    import sys

    asyncio.run(main())

输出

(mcp-client) D:\llm\MCP\mcp-client>python client.py D:\llm\MCP\weather\weather.py
Processing request of type ListToolsRequest

Connected to server with tools: [['get_alerts', 'Get weather alerts for a US state.\n\n    Args:\n        state: Two-letter US state code (e.g. CA, NY)\n    ', {'properties': {'state': {'title': 'State', 'type': 'string'}}, 'required': ['state'], 'title': 'get_alertsArguments', 'type': 'object'}], ['get_forecast', 'Get weather forecast for a location.\n\n    Args:\n        latitude: Latitude of the location\n        longitude: Longitude of the location\n    ', {'properties': {'latitude': {'title': 'Latitude', 'type': 'number'}, 'longitude': {'title': 'Longitude', 'type': 'number'}}, 'required': ['latitude', 'longitude'], 'title': 'get_forecastArguments', 'type': 'object'}]]

MCP Client Started!
Type your queries or 'quit' to exit.

Query: What are the weather alert in California
Processing request of type ListToolsRequest
{'content': None, 'refusal': None, 'role': 'assistant', 'audio': None, 'function_call': None, 'tool_calls': [{'id': 'call_-8960025703641360364', 'function': {'arguments': '{"state": "CA"}', 'name': 'get_alerts'}, 'type': 'function', 'index': 0}]}
Processing request of type CallToolRequest
HTTP Request: GET https://api.weather.gov/alerts/active/area/CA "HTTP/1.1 200 OK"
{'content': 'Here are the current weather alerts for California:\n\n**1. Wind Advisory**\n\n*   **Area:** Mojave Desert Slopes\n*   **Severity:** Moderate\n*   **Description:** West winds 20 to 30 mph with gusts up to 50 mph are expected from noon Wednesday to 7 AM PST Thursday. Gusty winds can blow around unsecured objects, and tree limbs could be blown down, potentially causing power outages.\n*   **Instructions:** Use extra caution while driving, especially for high-profile vehicles.\n\n**2. Lake Wind Advisory**\n\n*   **Area:** Greater Lake Tahoe Area\n*   **Severity:** Moderate\n*   **Description:** Southwest winds 15 to 25 mph with gusts up to 40 mph and waves 2 to 4 feet are expected for Lake Tahoe from 8 AM to 6 PM PST Wednesday. Small boats, kayaks, and paddleboards will be prone to capsizing.\n*   **Instructions:** Check lake conditions before heading out and consider postponing boating activities until conditions improve.\n\n**3. Wind Advisory**\n\n*   **Area:** Coastal Del Norte, Del Norte Interior, Southwestern Humboldt, Northern Humboldt Interior, Southern Humboldt Interior\n*   **Severity:** Moderate\n*   **Description:** South-southeast winds 25 to 35 mph with gusts up to 50 mph (locally up to 60 mph over higher terrain) are expected from 2 AM to 9 AM PST Wednesday. Wind gusts will be particularly strong along windward ridges and exposed coastal headlands.\n*   **Instructions:** Use extra caution while driving, especially for high-profile vehicles.\n\n**4. High Surf Advisory**\n\n*   **Area:** San Luis Obispo County Beaches, Santa Barbara County Central Coast Beaches\n*   **Severity:** Minor\n*   **Description:** Large breaking waves of 8 to 12 feet with dangerous rip currents are expected until 3 AM PST Wednesday.\n*   **Instructions:** Remain out of the water, or stay near occupied lifeguard towers. Stay off rock jetties.\n\n**5. High Surf Advisory**\n\n*   **Area:** Ventura County Beaches\n*   **Severity:** Minor\n*   **Description:** Large breaking waves of 6 to 9 feet with dangerous rip currents are expected until 3 AM PST Wednesday.\n*   **Instructions:** Remain out of the water, or stay near occupied lifeguard towers. Stay off rock jetties.\n\n**6. Wind Advisory**\n\n*   **Area:** Central Siskiyou County (including Interstate 5 from Grenada south to Weed, and the cities of Grenada, Gazelle, and Weed)\n*   **Severity:** Moderate\n*   **Description:** South winds 35 to 45 mph with gusts up to 60 mph are expected from 1 AM to 7 AM PST Wednesday. Gusty winds can blow around unsecured objects, and tree limbs could be blown down, potentially causing power outages.\n*   **Instructions:** Use extra caution while driving, especially for high-profile vehicles.\n\nThese alerts highlight various weather hazards across California, including high winds and dangerous surf conditions. Please heed the instructions provided in each alert to ensure your safety.\n', 'refusal': None, 'role': 'assistant', 'audio': None, 'function_call': None, 'tool_calls': None}

Here are the current weather alerts for California:

**1. Wind Advisory**

*   **Area:** Mojave Desert Slopes
*   **Severity:** Moderate
*   **Description:** West winds 20 to 30 mph with gusts up to 50 mph are expected from noon Wednesday to 7 AM PST Thursday. Gusty winds can blow around unsecured objects, and tree limbs could be blown down, potentially causing power outages.
*   **Instructions:** Use extra caution while driving, especially for high-profile vehicles.

**2. Lake Wind Advisory**

*   **Area:** Greater Lake Tahoe Area
*   **Severity:** Moderate
*   **Description:** Southwest winds 15 to 25 mph with gusts up to 40 mph and waves 2 to 4 feet are expected for Lake Tahoe from 8 AM to 6 PM PST Wednesday. Small boats, kayaks, and paddleboards will be prone to capsizing.
*   **Instructions:** Check lake conditions before heading out and consider postponing boating activities until conditions improve.

**3. Wind Advisory**

*   **Area:** Coastal Del Norte, Del Norte Interior, Southwestern Humboldt, Northern Humboldt Interior, Southern Humboldt Interior
*   **Severity:** Moderate
*   **Description:** South-southeast winds 25 to 35 mph with gusts up to 50 mph (locally up to 60 mph over higher terrain) are expected from 2 AM to 9 AM PST Wednesday. Wind gusts will be particularly strong along windward ridges and exposed coastal headlands.
*   **Instructions:** Use extra caution while driving, especially for high-profile vehicles.

**4. High Surf Advisory**

*   **Area:** San Luis Obispo County Beaches, Santa Barbara County Central Coast Beaches
*   **Severity:** Minor
*   **Description:** Large breaking waves of 8 to 12 feet with dangerous rip currents are expected until 3 AM PST Wednesday.
*   **Instructions:** Remain out of the water, or stay near occupied lifeguard towers. Stay off rock jetties.

**5. High Surf Advisory**

*   **Area:** Ventura County Beaches
*   **Severity:** Minor
*   **Description:** Large breaking waves of 6 to 9 feet with dangerous rip currents are expected until 3 AM PST Wednesday.
*   **Instructions:** Remain out of the water, or stay near occupied lifeguard towers. Stay off rock jetties.

**6. Wind Advisory**

*   **Area:** Central Siskiyou County (including Interstate 5 from Grenada south to Weed, and the cities of Grenada, Gazelle, and Weed)
*   **Severity:** Moderate
*   **Description:** South winds 35 to 45 mph with gusts up to 60 mph are expected from 1 AM to 7 AM PST Wednesday. Gusty winds can blow around unsecured objects, and tree limbs could be blown down, potentially causing power outages.
*   **Instructions:** Use extra caution while driving, especially for high-profile vehicles.

These alerts highlight various weather hazards across California, including high winds and dangerous surf conditions. Please heed the instructions provided in each alert to ensure your safety.

代码解释

代码功能概述

这是一个基于异步编程的MCP（可能是自定义协议）客户端程序，主要实现以下功能：

连接并控制通过Python/Node.js脚本实现的服务器
集成OpenAI API进行自然语言处理
支持工具扩展机制（通过服务器注册工具函数）
实现交互式聊天界面

关键组件解析

1. 类结构

class MCPClient:
    def __init__(self):
        self.session: Optional[ClientSession] = None  # 客户端会话
        self.exit_stack = AsyncExitStack()  # 异步资源管理器
        self.openai = OpenAI(...)  # OpenAI客户端

2. 核心方法

a. 服务器连接 (connect_to_server)

功能：通过标准输入输出与服务器建立连接

实现细节：

command = "python.exe" if Python脚本 else "node"  # 根据脚本类型选择解释器
server_params = StdioServerParameters(...)  # 配置服务器启动参数
stdio_transport = 建立标准输入输出管道
self.session = 创建客户端会话

b. 查询处理 (process_query)

工作流程：
1. 获取服务器注册的工具列表
2. 将工具信息转换为OpenAI兼容格式
3. 调用语言模型（示例中使用GLM-4模型）
4. 处理模型返回的工具调用请求
5. 整合工具调用结果生成最终响应

c. 交互循环 (chat_loop)

实现简单的REPL（Read-Eval-Print Loop）交互界面
支持输入"quit"退出

关键技术点

1. 异步架构

使用asyncio库实现非阻塞IO
AsyncExitStack管理异步资源生命周期
协程（coroutine）贯穿整个程序

2. 工具调用机制

response = await self.session.list_tools()  # 获取工具列表
available_tools = [...]  # 转换为OpenAI工具格式
model_response = openai.chat.completions.create(tools=available_tools)  # 带工具调用能力的模型请求

3. 服务集成

通过标准输入输出与子进程通信
支持Python和Node.js服务器脚本
示例服务器路径参数：python client.py path/to/server.py

执行流程

启动时加载环境变量（OPENAI_API_KEY等）
通过命令行参数指定服务器脚本
建立与服务器的连接

进入交互式聊天循环：

Query: 今天天气如何？
→ 模型判断需要调用天气查询工具
→ 调用服务器注册的天气工具
→ 整合工具结果生成最终响应

该代码展示了现代AI应用开发的典型模式：结合大语言模型与自定义工具扩展，通过异步架构实现高效交互。

注意事项：

 command = (
            "D:\\llm\\MCP\\mcp-client\\.venv\\Scripts\\python.exe"
            if is_python
            else "node"
        )

"D:\\llm\\MCP\\mcp-client\\.venv\\Scripts\\python.exe"为MCP Server代码解释器的路径

参考链接：https://modelcontextprotocol.io/quickstart/client