Gemini Image Generation MCP Server

This is a Model Context Protocol (MCP) server that provides image generation capabilities using Google's Gemini 2 API.

<a href="https://glama.ai/mcp/servers/@sanxfxteam/gemini-mcp-server"> <img width="380" height="200" src="https://glama.ai/mcp/servers/@sanxfxteam/gemini-mcp-server/badge" alt="Gemini Image Generation Server MCP server" /> </a>

Quick Start

1. Get Gemini API Key

   • Visit Google AI Studio
   • Create a new API key

2. Configure Claude Desktop

   • Locate your config file:

     Mac: ~/Library/Application Support/Claude/claude_desktop_config.json
     Windows: %APPDATA%\Claude\claude_desktop_config.json
     Linux: ~/.config/Claude/claude_desktop_config.json
     

   • Add Gemini configuration:

     {
       "mcpServers": {
         "gemini-imagen": {
           "command": "npx",
           "args": ["-y", "github:sanxfxteam/gemini-mcp-server"],
           "env": {
             "GEMINI_API_KEY": "your_api_key_here"
           }
         }
       }
     }
     

3. Restart Claude Desktop

Setup

1. Install dependencies:

npm install

2. Set up your environment variables: Create a .env file in the root directory and add your Google API key:

GEMINI_API_KEY=your_api_key_here

Usage

Run the server:

npm start

To test

npx @modelcontextprotocol/inspector npm run start

Available Tools

generateImage

Generates images using Gemini 2's experimental image generation API.

Parameters:

• prompt (string, required): The description of the image you want to generate
• numSamples (number, optional, default: 4): Number of images to generate
• aspectRatio (string, optional, default: '1:1'): Aspect ratio of the generated images
• personGeneration (string, optional, default: 'ALLOW_ADULT'): Person generation settings

Example MCP request:

{
  "tool": "generateImage",
  "params": {
    "prompt": "A serene mountain landscape at sunset",
    "numSamples": 2,
    "aspectRatio": "16:9"
  }
}

Notes

• This server uses the experimental image generation feature of Gemini 2
• Make sure you have appropriate access and API keys from Google
• The server communicates using the Model Context Protocol over stdio