Gemini Image Generation MCP Server

@collactivelabs

代码仓库

基本信息

分类

AI 与智能体

传输方式

stdio

作者

collactivelabs

关于 Gemini Image Generation MCP Server

A Model Calling Protocol (MCP) server that allows Claude and other LLMs to generate images using Google's Gemini AI model.

#gemini #image-generation #mcp

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": {
    "openai-image-generation": {
      "command": "node",
      "args": [
        "/full/path/to/openai-image-gen-mcp/src/mcp-server.js"
      ],
      "env": {
        "OPENAI_API_KEY": "your-openai-api-key-here"
      }
    }
  }
}

Gemini Image Generation MCP Server 工具

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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 Gemini Image Generation MCP?

Gemini Image Generation MCP is an MCP server that enables LLMs like Claude to generate images using Google's Gemini AI model (gemini-2.0-flash-preview-image-generation). It saves generated images locally and includes an interactive web interface for testing and demonstration.

How to use Gemini Image Generation MCP?

Install Node.js 18+, clone the repository, install dependencies (npm install), and set your GEMINI_API_KEY in the .env file. Run the MCP server with node src/mcp-server.js or use Docker. Configure Claude or another MCP client to connect via the MCP protocol—either through JSON configuration or the Claude console’s MCPs section.

Key features of Gemini Image Generation MCP

Generate images from text prompts using Google’s Gemini model.
Save generated images locally.
Configure generation parameters like temperature, topK, and topP.
Interactive web interface for testing and demonstration.
Docker support for easy deployment.
Simple MCP standard implementation.

Use cases of Gemini Image Generation MCP

Enable Claude to generate images as part of conversations.
Automate image creation for content generation pipelines.
Test and demo Gemini image generation capabilities via the web interface.
Integrate image generation into custom applications using the MCP protocol.

常见问题

What do I need to run this server?

You need Node.js 18 or higher and a Google API key with access to the Gemini API (specifically the image generation preview model). Docker is optional but supported.

How do I configure the server?

Create a `.env` file from `.env.example` and set `GEMINI_API_KEY` (required). Optional settings include `MCP_AUTH_TOKEN`, `PORT`, `OUTPUT_DIR`, and `LOG_LEVEL`.

How does the server integrate with Claude?

You can add the MCP server configuration in Claude’s settings via JSON or through the Claude console’s MCPs section, specifying the server URL and any authentication token.

Where are generated images saved?

By default, images are saved in the `./generated-images` directory, configurable via the `OUTPUT_DIR` environment variable.

What Gemini model is used for generation?

The server uses the `gemini-2.0-flash-preview-image-generation` model, which is optimized for image generation tasks.

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