# Nano Banana Pro MCP Server
[](https://opensource.org/licenses/MIT)
[](https://modelcontextprotocol.io)
An [MCP (Model Context Protocol)](https://modelcontextprotocol.io) 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](https://aistudio.google.com/apikey)
## Quick Start
### 1. Build the Docker Image
```bash
cd nano-banana-pro-mcp
docker build -t nano-banana-pro-mcp .
```
### 2. Create Output Directory
```bash
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)
```bash
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):
```json
{
"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 create
- `aspectRatio` (optional): 1:1, 2:3, 3:2, 3:4, 4:3, 4:5, 5:4, 9:16, 16:9, 21:9
- `resolution` (optional): 1K, 2K, or 4K
- `useGoogleSearch` (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 file
- `prompt` (required): Description of the modifications
- `referenceImages` (optional): Array of reference image paths
- `aspectRatio` (optional): Output aspect ratio
- `resolution` (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 modifications
- `referenceImages` (optional): Reference images for style transfer, etc.
- `aspectRatio` (optional): Output aspect ratio
- `resolution` (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 images
- `aspectRatio` (optional): Output aspect ratio
- `resolution` (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
1. **Be Descriptive**: The more detail in your prompt, the better the result
2. **Use Photography Terms**: For realistic images, mention camera angles, lens types, lighting
3. **Iterate**: Use `continue_editing` to refine images step by step
4. **Reference Images**: Use up to 14 reference images for character consistency or style transfer
5. **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:
```bash
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:
```bash
sudo chown -R $USER:$USER output
```
## Development
To run locally without Docker:
```bash
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](https://deepmind.google/technologies/gemini/) for the image generation API
- [Model Context Protocol](https://modelcontextprotocol.io) by Anthropic
- [Claude Code](https://claude.ai/code) for the amazing AI coding assistant
