mcp-use mcp server 交互工具

mcp-use mcp server 交互工具，当然mcp-use 不支持简单的mcp client，还支持agent开发，通过mcp-use 我们可以将llm 与mcp server 集成起来，提升agent 的能力

简单示例

import asyncio
import os
from dotenv import load_dotenv
from langchain_openai import ChatOpenAI
from mcp_use import MCPAgent, MCPClient

async def main():
    # Load environment variables
    load_dotenv()

    # Create configuration dictionary
    config = {
      "mcpServers": {
        "playwright": {
          "command": "npx",
          "args": ["@playwright/mcp@latest"],
          "env": {
            "DISPLAY": ":1"
          }
        }
      }
    }

    # Create MCPClient from configuration dictionary
    client = MCPClient.from_dict(config)

    # Create LLM
    llm = ChatOpenAI(model="gpt-4o")

    # Create agent with the client
    agent = MCPAgent(llm=llm, client=client, max_steps=30)

    # Run the query
    result = await agent.run(
        "Find the best restaurant in San Francisco USING GOOGLE SEARCH",
    )
    print(f"\nResult: {result}")

if __name__ == "__main__":
    asyncio.run(main())

说明

mcp-use 可以与langchain 集成，很值得尝试下

参考资料

https://github.com/mcp-use/mcp-use

https://docs.mcp-use.com/

https://docs.mcp-use.com/essentials/client-configuration