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MCP Multi-Server Demo with SSE Transport

@fredrikp999

代码仓库

基本信息

分类

AI 与智能体

传输方式

stdio

作者

fredrikp999

关于 MCP Multi-Server Demo with SSE Transport

Example of using MCP servers, both over sdio + sse. Also using langchain-mcp

#mcp#sse#langchain#multi-server#demo

MCP Multi-Server Demo with SSE Transport 配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

{
  "mcpServers": {
    "mcp-sse-langchain-example": {
      "command": "python",
      "args": [
        "main.py"
      ]
    }
  }
}

MCP Multi-Server Demo with SSE Transport 工具

工具列表暂未提供

当前收录暂时没有可展示的工具列表，不代表服务没有工具。请查阅项目文档了解支持的能力。

工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。

概览

What is MCP Multi-Server Demo with SSE Transport?

A demonstration project that uses the Model Context Protocol (MCP) to connect multiple servers via different transport methods (stdio and Server-Sent Events). It integrates with LangChain and OpenAI to create an agent that can use tools from both a math server and a weather server.

How to use MCP Multi-Server Demo with SSE Transport?

Clone the repository, install dependencies with pip install -r requirements.txt, and set your OpenAI API key in a .env file. Run python main.py to start the weather server on port 8000, connect to both servers, and execute example queries.

Key features of MCP Multi-Server Demo with SSE Transport

  • Math server with basic arithmetic operations (add, multiply)
  • Weather server providing simulated weather for different locations
  • MultiServerMCPClient to connect to servers with different transports
  • Integration with LangChain and OpenAI for agent functionality
  • Example queries for math and weather
  • Extensible: add more tools, servers, or real APIs

Use cases of MCP Multi-Server Demo with SSE Transport

  • Demonstrating how to use MCP with both stdio and SSE transports
  • Building a LangChain agent that can call tools from multiple MCP servers
  • Prototyping an assistant that combines math calculations and weather lookups
  • Learning how to extend MCP with custom server capabilities

常见问题

1

What does this demo do?

It shows how to connect multiple MCP servers using different transports (stdio and SSE) and create a LangChain agent that can use tools from both.

2

What are the dependencies?

Python 3.8+ and an OpenAI API key. Dependencies are installed via `requirements.txt`.

3

Where does the data live?

The weather data is simulated (no real API). All data is local to the demo.

4

What transport methods are used?

The math server uses stdio transport; the weather server uses SSE transport (HTTP-based server‑to‑client push).

5

How is authentication handled?

Only the OpenAI API key (set in `.env`) is required for the agent. No additional auth for the MCP servers.

评论

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