About Gemini Image Generation MCP
Gemini Image Generation MCP is a server for Claude and other LLM clients that generates images and videos with Google's Gemini models and Veo 2.0. It also includes a web interface, API, and paginated media gallery.
Key features
- 01Generate images from prompts
- 02Generate videos from prompts
- 03Animate images into videos
- 04Adjust generation parameters
- 05Save outputs locally
- 06Browse paginated media galleries
Use cases
- 01Create an image from a text description
- 02Generate a video from a prompt
- 03Animate an existing image
- 04Review previously generated media
MCP support
The server exposes image generation to MCP clients through the `generate_image` tool. The README also describes video generation capabilities and a separate REST API.
Configuration
Local server config is the same for every client. Copy it into your client’s MCP config file.
We haven’t collected a package or remote endpoint for this server. Follow the instructions in the project README.
Tools
Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.
Details
From the project READMEGemini Image & Video Generation MCP
A production-ready Model Context Protocol (MCP) server that enables Claude and other LLMs to generate images and videos using Google's Gemini AI models (Gemini 2.0 Flash and Veo 2.0).
🌟 Features
Core Capabilities
- ✨ Image Generation - Create images using Gemini 2.0 Flash (
gemini-2.0-flash-preview-image-generation) - 🎬 Video Generation - Generate videos using Veo 2.0 (
veo-2.0-generate-001) - 🎨 Image-to-Video - Animate images into videos with Veo 2.0
- 💾 Local Storage - Automatically save generated content
- ⚙️ Parameter Control - Fine-tune temperature, topK, and topP
Production Features
- 🔒 Optional Authentication - Token-based API security
- ⚡ Response Caching - 30-minute TTL cache for repeated prompts
- 📊 Rate Limiting - Prevent API abuse (100/15min general, 20/15min generation)
- ✅ Input Validation - Comprehensive request validation
- 📄 Pagination - Efficient gallery browsing with sorting
- 🔐 Configurable CORS - Environment-based origin control
- 📚 OpenAPI Documentation - Interactive Swagger UI at
/api-docs - 🧪 Test Suite - 17 automated tests with Jest
- 🐳 Docker Support - Easy containerized deployment
📋 Prerequisites
- Node.js 18 or higher
- Google API Key with access to:
- Gemini 2.0 Flash (image generation)
- Veo 2.0 (video generation)
- Docker (optional, for containerized deployment)
🚀 Quick Start
Installation
# Clone the repository
git clone https://github.com/your-org/gemini-image-gen-mcp.git
cd gemini-image-gen-mcp
# Install dependencies
npm install
# Configure environment
cp .env.example .env
# Edit .env and add your GEMINI_API_KEY
Running the Server
Option 1: Node.js (Development)
# MCP server only (for Claude integration)
npm start
# Web server with REST API + UI
npm run web
# Or use the start script
./start-server.sh --both # Both servers
./start-server.sh --mcp-only # MCP only
./start-server.sh --web-only # Web only
Option 2: Docker (Production)
docker-compose up -d
The web interface will be available at http://localhost:3070
🎯 API Endpoints
Generation Endpoints
POST /api/generate-image- Generate an image from a text promptPOST /api/generate-video- Generate a video from a text promptPOST /api/generate-video-from-image- Generate a video from an initial image
Gallery Endpoints
GET /api/images?page=1&limit=20- List generated images (paginated)GET /api/videos?page=1&limit=20- List generated videos (paginated)
System Endpoints
GET /health- Health checkGET /api-docs- Interactive Swagger UI documentationGET /api-docs.json- OpenAPI JSON specificationGET /api/cache/stats- View cache statisticsPOST /api/cache/clear- Clear response cache (requires auth)
📖 API Documentation
Interactive API documentation is available at:
- Swagger UI: http://localhost:3070/api-docs
- OpenAPI JSON: http://localhost:3070/api-docs.json
The Swagger UI provides:
- Complete endpoint documentation
- Request/response schemas
- Try-it-now functionality
- Authentication testing
- Parameter descriptions and examples
🔐 Authentication
Authentication is optional and can be enabled by setting the API_AUTH_TOKEN environment variable:
# In .env file
API_AUTH_TOKEN=your-secure-token-here
Using Authentication
Bearer Token (Recommended):
curl -H "Authorization: Bearer your-secure-token-here" \
-H "Content-Type: application/json" \
-d '{"prompt": "A sunset over mountains"}' \
http://localhost:3070/api/generate-image
Query Parameter (Alternative):
curl -X POST \
"http://localhost:3070/api/generate-image?token=your-secure-token-here" \
-H "Content-Type: application/json" \
-d '{"prompt": "A sunset over mountains"}'
⚙️ Configuration Options
All configuration is done via environment variables in .env:
| Variable | Description | Default |
|---|---|---|
GEMINI_API_KEY | Required - Google Gemini API key | - |
API_AUTH_TOKEN | Optional - API authentication token | - |
MCP_AUTH_TOKEN | Optional - MCP server authentication | - |
PORT | Web server port | 3070 |
OUTPUT_DIR | Base directory for generated files | ./generated-images |
LOG_LEVEL | Logging level (debug, info, warn, error) | info |
CORS_ORIGINS | Comma-separated allowed origins | * |
RATE_LIMIT_MAX | Max requests per 15min per IP | 100 |
GENERATION_RATE_LIMIT | Max generation requests per 15min | 20 |
ENABLE_CACHE | Enable response caching | true |
🧪 Testing
# Run all tests
npm test
# Run tests in watch mode
npm run test:watch
# Run tests with coverage report
npm run test:coverage
Current Test Coverage:
- 2 test suites
- 17 tests passing
- Coverage: Authentication, Tool Schemas, Input Validation
🐳 Docker Deployment
Using Docker Compose (Recommended)
# Start services
docker-compose up -d
# View logs
docker-compose logs -f
# Stop services
docker-compose down
Manual Docker Build
# Build image
docker build -t gemini-image-gen-mcp .
# Run container
docker run -d \
-p 3070:3070 \
-e GEMINI_API_KEY=your_key_here \
-v $(pwd)/generated-images:/app/generated-images \
-v $(pwd)/generated-videos:/app/generated-videos \
gemini-image-gen-mcp
🔌 Usage with Claude
Claude Desktop Configuration
Add to your Claude Desktop config file:
macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
Windows: %APPDATA%\Claude\claude_desktop_config.json
{
"mcpServers": {
"gemini-image-generation": {
"command": "node",
"args": ["/full/path/to/gemini-image-gen-mcp/src/mcp-server.js"],
"env": {
"GEMINI_API_KEY": "your-gemini-api-key-here"
}
}
}
}
Claude API Usage
# Example prompt to Claude
"Please generate an image of a serene mountain landscape at sunset using the Gemini image generation tool"
Claude will automatically invoke the MCP server's generate_image tool.
🎨 Web Interface
The web interface provides three main sections:
1. Generator Tab
- Enter text prompts for image/video generation
- Adjust generation parameters (temperature, topP, topK)
- Use sample prompts for quick testing
- View generation results with enhanced prompts
2. Gallery Tab
- Browse all generated images and videos
- Pagination support (20 items per page)
- Sorted by newest first
- Click to view full size
3. About Tab
- Project information
- Feature list
- Configuration details
- API documentation links
📊 Performance & Optimization
Response Caching
- Automatically caches successful generation results
- 30-minute TTL (configurable)
- Reduces API costs for repeated prompts
- Cache key includes: prompt + model + parameters
- View cache stats at
/api/cache/stats
Exponential Backoff
- Smart video polling (2s → 30s max)
- Reduces API calls by ~60%
- Prevents API rate limiting
Async I/O
- Non-blocking file operations
- Improved server responsiveness
- Better handling of concurrent requests
Pagination
- Constant memory usage
- Handles galleries with thousands of items
- Sorted by modification time
🛡️ Security Features
- ✅ Input Validation - All parameters validated with express-validator
- ✅ Rate Limiting - Two-tier system (general + generation specific)
- ✅ Request Size Limits - 10MB max to prevent DoS
- ✅ CORS Configuration - Environment-based origin control
- ✅ Optional Authentication - Token-based API security
- ✅ No Hardcoded Secrets - All credentials via environment variables
🔧 Troubleshooting
Common Issues
"GEMINI_API_KEY is not set" error:
# Make sure .env file exists and contains:
GEMINI_API_KEY=your_actual_key_here
Port already in use:
# Change port in .env file:
PORT=3080
Cache not working:
# Check cache is enabled in .env:
ENABLE_CACHE=true
# View cache stats:
curl http://localhost:3070/api/cache/stats
Rate limit exceeded:
# Increase limits in .env:
RATE_LIMIT_MAX=200
GENERATION_RATE_LIMIT=50
📝 Example API Requests
Generate an Image
curl -X POST http://localhost:3070/api/generate-image \
-H "Content-Type: application/json" \
-d '{
"prompt": "A futuristic cityscape at night with neon lights",
"temperature": 0.8,
"topP": 0.95,
"topK": 40
}'
Generate a Video
curl -X POST http://localhost:3070/api/generate-video \
-H "Content-Type: application/json" \
-d '{
"prompt": "A bird flying through a forest",
"temperature": 1.0
}'
List Images with Pagination
curl "http://localhost:3070/api/images?page=1&limit=10"
🤝 Contributing
Contributions are welcome! Please:
- Fork the repository
- Create a feature branch (
git checkout -b feature/amazing-feature) - Commit your changes (
git commit -m 'Add amazing feature') - Push to the branch (
git push origin feature/amazing-feature) - Open a Pull Request
Development Guidelines
- Run tests before committing:
npm test - Follow existing code style
- Update documentation for new features
- Add tests for new functionality
📄 License
ISC
🙏 Acknowledgments
- Built with Model Context Protocol
- Powered by Google Gemini AI
- Video generation using Veo 2.0
📞 Support
For issues and questions:
- Open an issue on GitHub
- Check the API Documentation
- Review the troubleshooting section above
Made with ❤️ for the AI community
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.