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Gemini Image Generation MCP Server

@sanxfxteam

代码仓库

基本信息

分类

AI 与智能体

许可证

MIT

传输方式

stdio

作者

sanxfxteam

关于 Gemini Image Generation MCP Server

Generate images using gemini

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

Gemini Image Generation 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。

点击上方按钮,在临时沙箱中运行此服务器并实时获取工具列表。

概览

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

常见问题

1

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.

2

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.

3

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.

4

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.

5

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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