nanobanana-mcp-server

# Nano Banana MCP Server 🍌 A production-ready **Model Context Protocol (MCP)** server that provides AI-powered image generation capabilities through Google's **Gemini** models with intelligent model selection. ## ⭐ NEW: Gemini 3 Pro Image Support! 🚀 Now featuring **Nano Banana Pro** - Google's latest and most powerful image generation model: - 🏆 **Professional 4K Quality**: Generate stunning images up to 3840px resolution - 🌐 **Google Search Grounding**: Access real-world knowledge for factually accurate images - 🧠 **Advanced Reasoning**: Configurable thinking levels for complex compositions - 🎯 **Superior Text Rendering**: Crystal-clear text in images at high resolution - 🎨 **Enhanced Understanding**: Better context comprehension for complex prompts <a href="https://glama.ai/mcp/servers/@zhongweili/nanobanana-mcp-server"> <img width="380" height="200" src="https://glama.ai/mcp/servers/@zhongweili/nanobanana-mcp-server/badge" alt="nanobanana-mcp-server MCP server" /> </a> ## ✨ Features - 🎨 **Multi-Model AI Image Generation**: Intelligent selection between Flash (speed) and Pro (quality) models - ⚡ **Gemini 2.5 Flash Image**: Fast generation (1024px) for rapid prototyping - 🏆 **Gemini 3 Pro Image**: High-quality up to 4K with Google Search grounding - 🤖 **Smart Model Selection**: Automatically chooses optimal model based on your prompt - 📐 **Aspect Ratio Control** ⭐ NEW: Specify output dimensions (1:1, 16:9, 9:16, 21:9, and more) - 📋 **Smart Templates**: Pre-built prompt templates for photography, design, and editing - 📁 **File Management**: Upload and manage files via Gemini Files API - 🔍 **Resource Discovery**: Browse templates and file metadata through MCP resources - 🛡️ **Production Ready**: Comprehensive error handling, logging, and validation - ⚡ **High Performance**: Optimized architecture with intelligent caching ## 🚀 Quick Start ### Prerequisites 1. **Google Gemini API Key** - [Get one free here](https://makersuite.google.com/app/apikey) 2. **Python 3.11+** (for development only) ### Installation Option 1: From MCP Registry (Recommended) This server is available in the [Model Context Protocol Registry](https://registry.modelcontextprotocol.io/?q=nanobanana). Search for "nanobanana" or use the MCP name below with your MCP client. mcp-name: io.github.zhongweili/nanobanana-mcp-server Option 2: Using `uvx` ```bash uvx nanobanana-mcp-server@latest ``` Option 3: Using `pip` ```bash pip install nanobanana-mcp-server ``` ## 🔧 Configuration ## ### Claude Desktop Add to your `claude_desktop_config.json`: ```json { "mcpServers": { "nanobanana": { "command": "uvx", "args": ["nanobanana-mcp-server@latest"], "env": { "GEMINI_API_KEY": "your-gemini-api-key-here" } } } } ``` **Configuration file locations:** - **macOS**: `~/Library/Application Support/Claude/claude_desktop_config.json` - **Windows**: `%APPDATA%\Claude\claude_desktop_config.json` ### Claude Code (VS Code Extension) Install and configure in VS Code: 1. Install the Claude Code extension 2. Open Command Palette (`Cmd/Ctrl + Shift + P`) 3. Run "Claude Code: Add MCP Server" 4. Configure: ```json { "name": "nanobanana", "command": "uvx", "args": ["nanobanana-mcp-server@latest"], "env": { "GEMINI_API_KEY": "your-gemini-api-key-here" } } ``` ### Cursor Add to Cursor's MCP configuration: ```json { "mcpServers": { "nanobanana": { "command": "uvx", "args": ["nanobanana-mcp-server@latest"], "env": { "GEMINI_API_KEY": "your-gemini-api-key-here" } } } } ``` ### Continue.dev (VS Code/JetBrains) Add to your `config.json`: ```json { "mcpServers": [ { "name": "nanobanana", "command": "uvx", "args": ["nanobanana-mcp-server@latest"], "env": { "GEMINI_API_KEY": "your-gemini-api-key-here" } } ] } ``` ### Open WebUI Configure in Open WebUI settings: ```json { "mcp_servers": { "nanobanana": { "command": ["uvx", "nanobanana-mcp-server@latest"], "env": { "GEMINI_API_KEY": "your-gemini-api-key-here" } } } } ``` ### Gemini CLI / Generic MCP Client ```bash # Set environment variable export GEMINI_API_KEY="your-gemini-api-key-here" # Run server in stdio mode uvx nanobanana-mcp-server@latest # Or with pip installation python -m nanobanana_mcp_server.server ``` ## 🤖 Model Selection Nano Banana supports two Gemini models with intelligent automatic selection: ### 🏆 Pro Model - Nano Banana Pro (Gemini 3 Pro Image) ⭐ NEW! **Google's latest and most advanced image generation model** - **Quality**: Professional-grade, production-ready - **Resolution**: Up to 4K (3840px) - highest available - **Speed**: ~5-8 seconds per image - **Special Features**: - 🌐 **Google Search Grounding**: Leverages real-world knowledge for accurate, contextual images - 🧠 **Advanced Reasoning**: Configurable thinking levels (LOW/HIGH) for complex compositions - 📐 **Media Resolution Control**: Fine-tune vision processing detail (LOW/MEDIUM/HIGH/AUTO) - 📝 **Superior Text Rendering**: Exceptional clarity for text-in-image generation - 🎨 **Enhanced Context Understanding**: Better interpretation of complex, narrative prompts - **Best for**: Production assets, marketing materials, professional photography, high-fidelity outputs, images requiring text, factual accuracy - **Cost**: Higher per image (premium quality) ### ⚡ Flash Model (Gemini 2.5 Flash Image) **Fast, reliable model for rapid iteration** - **Speed**: Very fast (2-3 seconds) - **Resolution**: Up to 1024px - **Quality**: High quality for everyday use - **Best for**: Rapid prototyping, iterations, high-volume generation, drafts, sketches - **Cost**: Lower per image ### 🤖 Automatic Selection (Recommended) By default, the server uses **AUTO** mode which intelligently analyzes your prompt and requirements: **Pro Model Selected When**: - Quality keywords detected: "4K", "professional", "production", "high-res", "HD" - High resolution requested: `resolution="4k"` or `resolution="high"` - Google Search grounding enabled: `enable_grounding=True` - High thinking level requested: `thinking_level="HIGH"` - Multi-image conditioning with multiple input images **Flash Model Selected When**: - Speed keywords detected: "quick", "draft", "sketch", "rapid" - High-volume batch generation: `n > 2` - Standard or lower resolution requested - No special Pro features required ### Usage Examples ```python # Automatic selection (recommended) "Generate a professional 4K product photo" # → Pro model (quality keywords + 4K) "Quick sketch of a cat" # → Flash model (speed keyword) "Create a diagram with clear text labels" # → Pro model (text rendering) "Draft mockup for website hero section" # → Flash model (draft keyword) # Explicit model selection generate_image( prompt="A scenic landscape", model_tier="flash" # Force Flash model for speed ) # Leverage Nano Banana Pro features generate_image( prompt="Professional product photo of vintage camera on wooden desk", model_tier="pro", # Use Pro model resolution="4k", # 4K resolution (Pro-only) thinking_level="HIGH", # Enhanced reasoning enable_grounding=True, # Use Google Search for accuracy media_resolution="HIGH" # High-detail vision processing ) # Pro model for high-quality text rendering generate_image( prompt="Infographic showing 2024 market statistics with clear labels", model_tier="pro", # Pro excels at text rendering resolution="4k" # Maximum clarity for text ) # Control aspect ratio for different formats ⭐ NEW! generate_image( prompt="Cinematic landscape at sunset", aspect_ratio="21:9" # Ultra-wide cinematic format ) generate_image( prompt="Instagram post about coffee", aspect_ratio="1:1" # Square format for social media ) generate_image( prompt="YouTube thumbnail design", aspect_ratio="16:9" # Standard video format ) generate_image( prompt="Mobile wallpaper of mountain vista", aspect_ratio="9:16" # Portrait format for phones ) ``` ### 📐 Aspect Ratio Control ⭐ NEW! Control the output image dimensions with the `aspect_ratio` parameter: **Supported Aspect Ratios**: - `1:1` - Square (Instagram, profile pictures) - `4:3` - Classic photo format - `3:4` - Portrait orientation - `16:9` - Widescreen (YouTube thumbnails, presentations) - `9:16` - Mobile portrait (phone wallpapers, stories) - `21:9` - Ultra-wide cinematic - `2:3`, `3:2`, `4:5`, `5:4` - Various photo formats ```python # Examples for different use cases generate_image( prompt="Product showcase for e-commerce", aspect_ratio="3:4", # Portrait format, good for product pages model_tier="pro" ) generate_image( prompt="Social media banner for Facebook", aspect_ratio="16:9" # Landscape banner format ) ``` **Note**: Aspect ratio works with both Flash and Pro models. For best results with specific aspect ratios at high resolution, use the Pro model with `resolution="4k"`. ## ⚙️ Environment Variables Configuration options: ```bash # Required GEMINI_API_KEY=your-gemini-api-key-here # Model Selection (optional) NANOBANANA_MODEL=auto # Options: flash, pro, auto (default: auto) # Optional IMAGE_OUTPUT_DIR=/path/to/image/directory # Default: ~/nanobanana-images LOG_LEVEL=INFO # DEBUG, INFO, WARNING, ERROR LOG_FORMAT=standard # standard, json, detailed ``` ## 🐛 Troubleshooting ### Common Issues **"GEMINI_API_KEY not set"** - Add your API key to the MCP server configuration in your client - Get a free API key at [Google AI Studio](https://makersuite.google.com/app/apikey) **"Server failed to start"** - Ensure you're using the latest version: `uvx nanobanana-mcp-server@latest` - Check that your client supports MCP (Claude Desktop 0.10.0+) **"Permission denied" errors** - The server creates images in `~/nanobanana-images` by default - Ensure write permissions to your home directory ### Development Setup For local development: ```bash # Clone repository git clone https://github.com/zhongweili/nanobanana-mcp-server.git cd nanobanana-mcp-server # Install with uv uv sync # Set environment export GEMINI_API_KEY=your-api-key-here # Run locally uv run python -m nanobanana_mcp_server.server ``` ## 📄 License MIT License - see [LICENSE](LICENSE) for details. ## 🆘 Support - **Issues**: [GitHub Issues](https://github.com/zhongweili/nanobanana-mcp-server/issues) - **Discussions**: [GitHub Discussions](https://github.com/zhongweili/nanobanana-mcp-server/discussions)