The MCP NanoBanana server provides AI-powered image generation and editing through Google's Nano Banana model via the AceDataCloud API, accessible from MCP-compatible clients like Claude Desktop or VS Code.
Image Generation: Create high-quality photorealistic or artistic images from detailed text prompts that include subject, atmosphere, lighting, camera/lens specifications, and quality keywords.
Image Editing & Manipulation: Edit existing images, combine multiple images, perform virtual try-on (placing clothing on people), product placement in scenes, attribute replacement (materials, colors, styles), image restoration, 2D to 3D conversion for product mockups, and rapid poster editing.
Task Management: Query individual or batch task status, retrieve results with image URLs and metadata, and optionally use webhook callbacks for asynchronous result delivery without polling.
Input Flexibility: Work with images via HTTP/HTTPS URLs or base64-encoded data, supporting multiple source images for complex editing operations.
Integration: Configurable API endpoints, timeouts, and logging for seamless integration with MCP-enabled applications.
Provides tools for AI image generation and editing using Google's Nano Banana model, supporting text-to-image creation, virtual try-on, and product placement within realistic scenes.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@MCP NanoBananagenerate a photorealistic neon-lit ramen shop in Tokyo at night"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
MCP NanoBanana
A Model Context Protocol (MCP) server for AI image generation and editing using Google's Nano Banana model through the AceDataCloud API.
Generate and edit AI images directly from Claude, VS Code, or any MCP-compatible client.
Features
Image Generation - Create high-quality images from text prompts
Image Editing - Modify existing images or combine multiple images
Virtual Try-On - Put clothing on people in photos
Product Placement - Place products in realistic scenes
Task Tracking - Monitor generation progress and retrieve results
Quick Start
1. Get API Token
Get your API token from AceDataCloud Platform:
Sign up or log in
Navigate to Nano Banana Images API
Click "Acquire" to get your token
2. Install
# Clone the repository
git clone https://github.com/AceDataCloud/MCPNanoBanana.git
cd MCPNanoBanana
# Install with pip
pip install -e .
# Or with uv (recommended)
uv pip install -e .3. Configure
# Copy example environment file
cp .env.example .env
# Edit with your API token
echo "ACEDATACLOUD_API_TOKEN=your_token_here" > .env4. Run
# Run the server
mcp-nanobanana-pro
# Or with Python directly
python main.pyClaude Desktop Integration
Add to your Claude Desktop configuration:
macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
Windows: %APPDATA%\Claude\claude_desktop_config.json
{
"mcpServers": {
"nanobanana": {
"command": "mcp-nanobanana-pro",
"env": {
"ACEDATACLOUD_API_TOKEN": "your_api_token_here"
}
}
}
}Or if using uv:
{
"mcpServers": {
"nanobanana": {
"command": "uv",
"args": ["run", "--directory", "/path/to/MCPNanoBanana", "mcp-nanobanana-pro"],
"env": {
"ACEDATACLOUD_API_TOKEN": "your_api_token_here"
}
}
}
}Available Tools
Image Generation
Tool | Description |
| Generate an image from a text prompt |
| Edit or combine images with AI |
Tasks
Tool | Description |
| Query a single task status |
| Query multiple tasks at once |
Usage Examples
Generate Image from Prompt
User: Create an image of a sunset over mountains
Claude: I'll generate that image for you.
[Calls nanobanana_generate_image with detailed prompt]Virtual Try-On
User: Put this shirt on this model
[Provides two image URLs]
Claude: I'll combine these images.
[Calls nanobanana_edit_image with both image URLs]Product Photography
User: Place this product in a modern kitchen scene
[Provides product image URL]
Claude: I'll create a product scene for you.
[Calls nanobanana_edit_image with scene description]Prompt Writing Tips
For best results, include these elements in your prompts:
Main Subject: What is the primary focus?
Atmosphere: What mood should the image convey?
Lighting: How is the scene illuminated?
Camera/Lens: What photographic style? (85mm portrait, wide-angle, etc.)
Quality Keywords: Technical descriptors (bokeh, film grain, HDR, etc.)
Example Prompt
A photorealistic close-up portrait of an elderly Japanese ceramicist
with deep wrinkles and a warm smile. Soft golden hour light streaming
through a window. Captured with an 85mm portrait lens, soft bokeh
background. Serene and masterful mood.Configuration
Environment Variables
Variable | Description | Default |
| API token from AceDataCloud | Required |
| API base URL |
|
| Request timeout in seconds |
|
| Logging level |
|
Command Line Options
mcp-nanobanana-pro --help
Options:
--version Show version
--transport Transport mode: stdio (default) or http
--port Port for HTTP transport (default: 8000)Development
Setup Development Environment
# Clone repository
git clone https://github.com/AceDataCloud/MCPNanoBanana.git
cd MCPNanoBanana
# Create virtual environment
python -m venv .venv
source .venv/bin/activate # or `.venv\Scripts\activate` on Windows
# Install with dev dependencies
pip install -e ".[dev,test]"Run Tests
# Run unit tests
pytest
# Run with coverage
pytest --cov=core --cov=tools
# Run integration tests (requires API token)
pytest tests/test_integration.py -m integrationCode Quality
# Format code
ruff format .
# Lint code
ruff check .
# Type check
mypy core toolsBuild & Publish
# Install build dependencies
pip install -e ".[release]"
# Build package
python -m build
# Upload to PyPI
twine upload dist/*Project Structure
NanoBanana/
├── core/ # Core modules
│ ├── __init__.py
│ ├── client.py # HTTP client for NanoBanana API
│ ├── config.py # Configuration management
│ ├── exceptions.py # Custom exceptions
│ ├── server.py # MCP server initialization
│ ├── types.py # Type definitions
│ └── utils.py # Utility functions
├── tools/ # MCP tool definitions
│ ├── __init__.py
│ ├── image_tools.py # Image generation/editing tools
│ └── task_tools.py # Task query tools
├── prompts/ # MCP prompt templates
│ └── __init__.py
├── tests/ # Test suite
├── .env.example # Environment template
├── .gitignore
├── LICENSE
├── main.py # Entry point
├── pyproject.toml # Project configuration
└── README.mdAPI Reference
This server wraps the AceDataCloud NanoBanana API:
NanoBanana Images API - Image generation and editing
NanoBanana Tasks API - Task queries
Use Cases
Portrait Enhancement - Try different clothing on the same person
Product Scene Composition - Place white-background products in realistic environments
Attribute Replacement - Change materials, colors, or variants
Poster Quick Editing - Rapidly change styles or themes
2D to 3D Conversion - Convert images to 3D product mockups
Image Restoration - Restore old or damaged photos
Contributing
Contributions are welcome! Please:
Fork the repository
Create a feature branch (
git checkout -b feature/amazing)Commit your changes (
git commit -m 'Add amazing feature')Push to the branch (
git push origin feature/amazing)Open a Pull Request
License
MIT License - see LICENSE for details.
Links
Made with love by AceDataCloud