Nano Banana Pro MCP Server
Brings Google Gemini 2.0 Flash native image generation capabilities into Claude Code, enabling users to generate, edit, compose, and iteratively refine images using natural language prompts directly from their coding environment.
README
Nano Banana Pro MCP Server
An MCP (Model Context Protocol) server that brings Google Gemini 2.0 Flash native image generation capabilities directly into Claude Code and other MCP-compatible AI assistants.
Generate, edit, and compose images using natural language - all without leaving your coding environment.
Features
- Generate Images: Create high-quality images from text prompts (up to 4K resolution)
- Edit Images: Modify existing images with text instructions
- Continue Editing: Iteratively refine the last generated image
- Compose Images: Combine up to 14 reference images into new compositions
- Google Search Grounding: Generate images based on real-time information
- Multiple Aspect Ratios: Support for 1:1, 16:9, 9:16, 4:3, 3:4, and more
- High Resolution: Output at 1K, 2K, or 4K resolution
Prerequisites
- Docker Desktop installed and running
- Gemini API key from Google AI Studio
Quick Start
1. Build the Docker Image
cd nano-banana-pro-mcp
docker build -t nano-banana-pro-mcp .
2. Create Output Directory
mkdir -p output input
3. Add to Claude Code
Add the MCP server to Claude Code using one of these methods:
Option A: Using claude mcp add (Recommended)
claude mcp add nano-banana-pro \
--transport stdio \
-- docker run -i --rm \
-e GEMINI_API_KEY=$GEMINI_API_KEY \
-v $(pwd)/output:/output \
-v $(pwd)/input:/input:ro \
nano-banana-pro-mcp
Option B: Manual Configuration
Add to your Claude Code MCP configuration file (~/.claude/claude_desktop_config.json or similar):
{
"mcpServers": {
"nano-banana-pro": {
"command": "docker",
"args": [
"run", "-i", "--rm",
"-e", "GEMINI_API_KEY",
"-v", "/path/to/output:/output",
"-v", "/path/to/input:/input:ro",
"nano-banana-pro-mcp"
],
"env": {
"GEMINI_API_KEY": "your-api-key-here"
}
}
}
}
Available Tools
generate_image
Generate a new image from a text prompt.
Parameters:
prompt(required): Text description of the image to createaspectRatio(optional): 1:1, 2:3, 3:2, 3:4, 4:3, 4:5, 5:4, 9:16, 16:9, 21:9resolution(optional): 1K, 2K, or 4KuseGoogleSearch(optional): Enable real-time information grounding
Example:
Generate a professional hero image for a tech startup website, showing a
modern office with developers collaborating, 16:9 aspect ratio, 2K resolution
edit_image
Edit an existing image with text instructions.
Parameters:
imagePath(required): Path to the image fileprompt(required): Description of the modificationsreferenceImages(optional): Array of reference image pathsaspectRatio(optional): Output aspect ratioresolution(optional): Output resolution
Example:
Edit /input/logo.png - Change the background color to gradient blue and
add a subtle glow effect around the text
continue_editing
Continue editing the last generated/edited image.
Parameters:
prompt(required): Description of additional modificationsreferenceImages(optional): Reference images for style transfer, etc.aspectRatio(optional): Output aspect ratioresolution(optional): Output resolution
Example:
Make the colors more vibrant and add a subtle drop shadow
compose_images
Combine multiple images into a new composition.
Parameters:
images(required): Array of image paths (up to 14)prompt(required): How to combine the imagesaspectRatio(optional): Output aspect ratioresolution(optional): Output resolution
Example:
Compose these product photos into a professional catalog layout
with consistent lighting and white background
get_last_image_info
Get information about the last generated image.
get_configuration_status
Check if the API key is configured.
Tips for Best Results
- Be Descriptive: The more detail in your prompt, the better the result
- Use Photography Terms: For realistic images, mention camera angles, lens types, lighting
- Iterate: Use
continue_editingto refine images step by step - Reference Images: Use up to 14 reference images for character consistency or style transfer
- Google Search: Enable for real-time data like weather, news, or current events
Output Location
Generated images are saved to the /output directory (mounted from ./output on your host).
Troubleshooting
"GEMINI_API_KEY not set"
Make sure your API key is set in your environment:
export GEMINI_API_KEY="your-key-here"
Images not appearing
Check the ./output directory on your host machine. Ensure the volume mount is correct.
Docker permission issues
On Linux, you may need to run:
sudo chown -R $USER:$USER output
Development
To run locally without Docker:
npm install
npm run build
GEMINI_API_KEY=your-key OUTPUT_DIR=./output npm start
Contributing
Contributions are welcome! Please feel free to submit a Pull Request.
License
MIT
Acknowledgments
- Google Gemini for the image generation API
- Model Context Protocol by Anthropic
- Claude Code for the amazing AI coding assistant
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