gemini-mcp-server

# 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](https://makersuite.google.com/app/apikey) - 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: ```json { "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: ```bash 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: ```bash npm start ``` To test ```bash 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: ```json { "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