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MCP Gemini Server

@amitsh06

リポジトリ

基本情報

カテゴリ

AI とエージェント

トランスポート

stdio

作者

amitsh06

MCP Gemini Server について

概要はまだありません

MCP Gemini 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-server-amitsh06": {
      "command": "python",
      "args": [
        "-m",
        "venv",
        "venv"
      ]
    }
  }
}

MCP Gemini 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 MCP Gemini Server?

MCP Gemini Server is an implementation of the Model Context Protocol (MCP) that enables AI assistants like Claude to interact with Google's Gemini API. It allows AI assistants to request text generation, text analysis, and maintain chat conversations through the Gemini API.

How to use MCP Gemini Server?

Install Python 3.7+ and obtain a Google AI API key. Clone the repository, create a virtual environment, install dependencies, and set your API key in a .env file as GEMINI_API_KEY. Start the server with python server.py, then send POST requests to the /mcp endpoint with a JSON payload containing the action and parameters.

Key features of MCP Gemini Server

  • Implements MCP protocol for secure message exchange.
  • Generates text via Gemini with configurable temperature and max tokens.
  • Analyzes text for sentiment, summary, keywords, or general analysis.
  • Supports multi-turn chat conversations with Gemini.
  • Uses .env file for secure API key storage.
  • Provides health check and model listing endpoints.

Use cases of MCP Gemini Server

  • AI assistants generating creative content like poems or stories.
  • Analyzing sentiment of user-provided text.
  • Conducting interactive Q&A sessions with context.
  • Summarizing documents or extracting keywords.
  • Enabling Claude to leverage Gemini's text capabilities.

よくある質問

1

What actions does MCP Gemini Server support?

It supports three actions: `generate_text`, `analyze_text`, and `chat`.

2

What parameters are required for text generation?

You must provide a `prompt`. Optional parameters include `temperature` (0.0 to 1.0) and `max_tokens`.

3

What analysis types are available?

The `analysis_type` parameter can be `'sentiment'`, `'summary'`, `'keywords'`, or `'general'`.

4

How do I start the server?

Run `python server.py` after installing dependencies and setting your `GEMINI_API_KEY` in a `.env` file.

5

What HTTP endpoints does the server expose?

It exposes `GET /health`, `GET /list-models`, and `POST /mcp` as the main endpoint for MCP requests.

コメント

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