Gemini Image Generation MCP Server

@sanxfxteam

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

sanxfxteam

Gemini Image Generation MCP Server について

Generate images using gemini

Gemini Image Generation 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": {
    "gemini-mcp-server-sanxfxteam": {
      "command": "npx",
      "args": [
        "@modelcontextprotocol/inspector",
        "npm",
        "run",
        "start"
      ]
    }
  }
}

Gemini Image Generation 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。

上のボタンで一時的なサンドボックスでこのサーバーを実行し、ツール一覧を取得できます。

概要

What is Gemini Image Generation MCP Server?

It is a Model Context Protocol (MCP) server that provides image generation capabilities using Google's Gemini 2 API. Designed for developers and Claude Desktop users who want to generate images directly from MCP-compatible tools.

How to use Gemini Image Generation MCP Server?

Obtain a Gemini API key from Google AI Studio, then configure Claude Desktop by adding the server entry to its config file with the GEMINI_API_KEY environment variable. Restart Claude Desktop and invoke the generateImage tool with a required prompt and optional parameters (numSamples, aspectRatio, personGeneration). Alternatively, run the server locally with npm start.

Key features of Gemini Image Generation MCP Server

Generates images using Gemini 2’s experimental image generation API
Provides a single generateImage tool with required prompt
Supports configurable number of samples (default 4)
Supports aspect ratio options (default 1:1)
Supports person generation settings (default ALLOW_ADULT)

Use cases of Gemini Image Generation MCP Server

Generate custom visuals directly from Claude Desktop using natural language prompts
Quickly produce multiple image variations for content or design ideas
Integrate image generation into MCP‑based workflows or automation

よくある質問

What does this server do?

It acts as an MCP-compatible bridge that sends image generation requests to Google’s Gemini 2 experimental API and returns the resulting images.

What are the runtime requirements?

You need Node.js, npm, a valid Google Gemini API key, and an internet connection. The server runs over stdio via the MCP transport.

Where does generated image data live?

Images are generated remotely by Google’s Gemini API; the server only passes requests and responses. No persistent storage is handled by the server.

Is the image generation feature stable?

The server uses the **experimental** image generation feature of Gemini 2, so behavior may change. Ensure you have appropriate API access from Google.

How is authentication handled?

Authentication is done via a `GEMINI_API_KEY` environment variable set in the MCP server configuration or in a `.env` file.

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