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MCP Server

@drkhan107

リポジトリ

基本情報

カテゴリ

AI とエージェント

ライセンス

MIT

トランスポート

stdio

作者

drkhan107

MCP Server について

A working pattern for SSE-based MCP clients and servers using Gemini LLM

MCP Server の設定

以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。

{
  "mcpServers": {
    "mcp_gemini": {
      "command": "python",
      "args": [
        "sse_server.py"
      ]
    }
  }
}

MCP Server のツール

ツール一覧はまだありません

この掲載には表示できるツール一覧がまだありません。サーバーにツールがないという意味ではありません。対応機能はプロジェクトのドキュメントをご確認ください。

ツールは README から自動的に抽出されます。メンテナーは ## Tools という見出しの下に記載することで、このタブに反映できます。

概要

What is Model Context Protocol (MCP)?

A working demo of the Model Context Protocol integrated with Google’s Gemini. It provides a server that uses SSE (Server-Sent Events) to expose MCP endpoints, alongside a FastAPI backend and a Streamlit GUI for interacting with the system.

How to use Model Context Protocol (MCP)?

Clone the repository, set a GOOGLE_API_KEY in a .env file, install dependencies with pip install -r requirements.txt, then start the MCP server with python sse_server.py (defaults to http://localhost:8080/sse). Optionally launch the SSE client with python ssc_client.py http://localhost:8080/sse, start the FastAPI server with python fastapp.py, and finally run the Streamlit app with streamlit run app.py (opens on localhost:8501). Click “Connect to MCP server” in the browser.

Key features of Model Context Protocol (MCP)

  • Integrates with Google’s Gemini.
  • Uses SSE (Server-Sent Events) transport.
  • Includes a FastAPI server for a GUI backend.
  • Provides a Streamlit web interface.
  • Simple setup with a .env file for API key.
  • Fully functional demo ready to run locally.

Use cases of Model Context Protocol (MCP)

  • Experimenting with MCP and Gemini in a local environment.
  • Building a chat-like GUI that connects to an MCP server.
  • Prototyping applications that combine context management with Google’s generative AI.
  • Learning how to set up an MCP server with SSE and a client.

よくある質問

1

What transport does the MCP server use?

The server uses SSE (Server-Sent Events) and runs by default on `http://localhost:8080/sse`.

2

Do I need an API key to run this server?

Yes, you must add a valid Google API key to a `.env` file as `GOOGLE_API_KEY`.

3

How do I start the GUI?

First ensure the MCP server and FastAPI server are running, then launch the Streamlit app with `streamlit run app.py` and open `localhost:8501` in your browser.

4

What dependencies are required?

All dependencies are listed in `requirements.txt` and can be installed with `pip install -r requirements.txt`.

コメント

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