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MCP 学习项目

@uoky5217

代码仓库

基本信息

分类

其他

传输方式

stdio

作者

uoky5217

关于 MCP 学习项目

个人学习MCP

MCP 学习项目 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-Server-Study": {
      "command": "python",
      "args": [
        "main.py"
      ]
    }
  }
}

MCP 学习项目 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 学习项目⚡?

MCP 学习项目⚡ is a learning project based on the Model Context Protocol (MCP) that demonstrates how to implement an MCP Server. It includes a FastAPI-based API server simulating a Java backend with basic arithmetic operations (addition, subtraction, multiplication, division), and two MCP server implementations — one using the stdio transport and another using the SSE (Server-Sent Events) transport. The project is intended for developers who want to learn MCP server development and testing.

How to use MCP 学习项目⚡?

To use the stdio mode, first run python main.py in the api_server directory to start the API service, then configure the MCP server in Cline with the provided stdio transport configuration. For SSE mode, after starting the API service, run python remote_server.py in the mcp_server directory to start the MCP server, then configure Cline with the SSE transport URL (http://127.0.0.1:8001/sse). In both cases, test the MCP server inside the Cline plugin.

Key features of MCP 学习项目⚡

  • Arithmetic toolset: add, subtract, multiply, divide
  • SSE-based real‑time message transport
  • Async HTTP client (HTTPX) support
  • Strong type input validation
  • Two transport implementations: stdio and SSE

Use cases of MCP 学习项目⚡

  • Learning how to build and configure an MCP Server
  • Practicing MCP integration with the Cline plugin
  • Understanding the difference between stdio and SSE transports
  • Writing and running pytest unit tests for API endpoints

常见问题

1

What transport modes does MCP 学习项目⚡ support?

It supports two transport modes: stdio (local invocation via command line) and SSE (remote server using Uvicorn on port 8001).

2

What are the runtime dependencies?

Python 3.10+, the uv package manager, and dependencies listed in `requirements.txt`: Starlette (framework), Uvicorn (server), HTTPX (HTTP client), and the MCP Server‑Sent Transports library.

3

Where does the data live?

Data is simulated locally by the FastAPI API server; no external database is used. The API server runs on port 8000 and handles arithmetic requests.

4

Are there any limitations?

The project currently implements only basic arithmetic operations (add, subtract, multiply, divide). It is a learning project, not intended for production use.

5

How is authentication handled?

The README does not mention any authentication mechanisms for the MCP or API servers.

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