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MyMCP Prompt MCP Server

@AlexJ-StL

代码仓库

基本信息

分类

其他

传输方式

stdio

作者

AlexJ-StL

关于 MyMCP Prompt MCP Server

MyMCP Prompt is a tool for generating Model Context Protocol (MCP) servers from natural language descriptions. This MVP uses the Google Gemini API to convert user descriptions into functional Python MCP servers with corresponding JSON configurations.

MyMCP Prompt MCP Server 配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

{
  "mcpServers": {
    "mymcp-alexj-stl": {
      "command": "uv",
      "args": [
        "venv"
      ]
    }
  }
}

MyMCP Prompt MCP Server 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 MyMCP Prompt?

MyMCP Prompt is a tool for generating Model Context Protocol (MCP) servers from natural language descriptions. It uses the Google Gemini API to convert user descriptions into functional Python MCP servers with corresponding JSON configurations. The application consists of a Flask backend and a React frontend built with Vite.

How to use MyMCP Prompt?

Clone the repository, set up the Python virtual environment and install dependencies, then install Node.js dependencies for the frontend. Set the GEMINI_API_KEY environment variable with a valid Google Gemini API key. Start the Flask backend with flask run and the frontend dev server with npm run dev. Open http://localhost:5173, enter a server description, and click "Place Your Order" to generate the server code and configuration.

Key features of MyMCP Prompt

  • Generates MCP server code from natural language descriptions.
  • Uses the Google Gemini API for text-to-code conversion.
  • Provides a Flask backend with a /api/generate-mcp endpoint.
  • Frontend built with React and Vite (French café-themed UI).
  • Saves generated Python code and JSON configuration to files.
  • Backend chooses the output directory automatically.

Use cases of MyMCP Prompt

  • Quickly prototyping a custom MCP server without manual coding.
  • Generating a server for a specific task by describing it in plain English.
  • Learning how MCP servers are structured by reviewing generated code and config.
  • Rapidly iterating on server ideas during development.

常见问题

1

What does MyMCP Prompt generate?

It generates a complete Python MCP server script and a corresponding JSON configuration file based on a user-written description.

2

What are the runtime dependencies?

Python packages listed in `requirements.txt` (Flask, Google Generative AI client, etc.) and Node.js dependencies for the frontend (Vite, React). A Google Gemini API key is also required.

3

How do I set the Gemini API key?

Set the environment variable `GEMINI_API_KEY` to your key before starting the backend. On Windows, use `set GEMINI_API_KEY=your_key`; on macOS/Linux, add `export GEMINI_API_KEY="your_key"` to your shell config.

4

Where are the generated files saved?

The files are saved to a directory chosen by the backend LLM (the current version does not let the user specify an output directory). The frontend displays the saved file paths.

5

Which LLM does MyMCP Prompt use?

Currently, only the Google Gemini API is supported. Future versions plan to integrate additional LLMs (OpenRouter, OpenAI, Anthropic, etc.).

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