io.github.AceDataCloud/mcp-nanobanana-pro
MCP server for NanoBanana AI image generation and editing
Open source Repository Open in the app JSON README (API)
About
MCP server for NanoBanana AI image generation and editing
Details
- Kind
- MCP servers
- Topic
- AI, RAG & memory
- Publisher
- acedatacloud
- Origin
- official
- Category
- ferramentas
- Transport
- http
- Version
- 2026.9.5.0
- Stars
- 7
- Forks
- 1
- Open pull requests
- 8
- Last push
- 2026-09-05T12:23:32Z
- Repository state
- ativo
- Language
- Python
- License
- MIT
- Added
- 2026-08-29 03:01:40
- Updated
- 2026-09-05 13:00:12
- Origin id
io.github.AceDataCloud/mcp-nanobanana-pro
README
# NanoBananaMCP
<!-- mcp-name: io.github.AceDataCloud/mcp-nanobanana-pro -->
[](https://pypi.org/project/mcp-nanobanana-pro/)
[](https://pypi.org/project/mcp-nanobanana-pro/)
[](https://www.python.org/downloads/)
[](https://opensource.org/licenses/MIT)
[](https://modelcontextprotocol.io)
A [Model Context Protocol (MCP)](https://modelcontextprotocol.io) server for AI image generation and editing using [Google's Nano Banana](https://deepmind.google/technologies/imagen/) model through the [AceDataCloud API](https://platform.acedata.cloud).
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
## Tool Reference
| Tool | Description |
|------|-------------|
| `nanobanana_generate_image` | Generate an AI image from a text prompt using Google's Nano Banana model. |
| `nanobanana_edit_image` | Edit or combine images using AI based on a text prompt. |
| `nanobanana_get_task` | Query the status and result of an image generation or edit task. |
| `nanobanana_get_tasks_batch` | Query multiple image generation/edit tasks at once. |
## Quick Start
### 1. Get Your API Token
1. Sign up at [AceDataCloud Platform](https://platform.acedata.cloud)
2. Go to the [API documentation page](https://platform.acedata.cloud/documents/nano-banana-images)
3. Click **"Acquire"** to get your API token
4. Copy the token for use below
### 2. Use the Hosted Server (Recommended)
AceDataCloud hosts a managed MCP server — **no local installation required**.
**Endpoint:** `https://nanobanana.mcp.acedata.cloud/mcp`
All requests require a Bearer token. Use the API token from Step 1.
#### Claude.ai
Connect directly on [Claude.ai](https://claude.ai) with OAuth — **no API token needed**:
1. Go to Claude.ai **Settings → Integrations → Add More**
2. Enter the server URL: `https://nanobanana.mcp.acedata.cloud/mcp`
3. Complete the OAuth login flow
4. Start using the tools in your conversation
#### Claude Desktop
Add to your config (`~/Library/Application Support/Claude/claude_desktop_config.json` on macOS):
```json
{
"mcpServers": {
"nanobanana": {
"type": "streamable-http",
"url": "https://nanobanana.mcp.acedata.cloud/mcp",
"headers": {
"Authorization": "Bearer YOUR_API_TOKEN"
}
}
}
}
```
#### Cursor / Windsurf
Add to your MCP config (`.cursor/mcp.json` or `.windsurf/mcp.json`):
```json
{
"mcpServers": {
"nanobanana": {
"type": "streamable-http",
"url": "https://nanobanana.mcp.acedata.cloud/mcp",
"headers": {
"Authorization": "Bearer YOUR_API_TOKEN"
}
}
}
}
```
#### VS Code (Copilot)
Add to your VS Code MCP config (`.vscode/mcp.json`):
```json
{
"servers": {
"nanobanana": {
"type": "streamable-http",
"url": "https://nanobanana.mcp.acedata.cloud/mcp",
"headers": {
"Authorization": "Bearer YOUR_API_TOKEN"
}
}
}
}
```
Or install the [Ace Data Cloud MCP extension](https://marketplace.visualstudio.com/items?itemName=acedatacloud.acedatacloud-mcp) for VS Code, which registers the hosted MCP servers with one-click setup.
#### JetBrains IDEs
1. Go to **Settings → Tools → AI Assistant → Model Context Protocol (MCP)**
2. Click **Add** → **HTTP**
3. Paste:
```json
{
"mcpServers": {
"nanobanana": {
"url": "https://nanobanana.mcp.acedata.cloud/mcp",
"headers": {
"Authorization": "Bearer YOUR_API_TOKEN"
}
}
}
}
```
#### Claude Code
Claude Code supports MCP servers natively:
```bash
claude mcp add nanobanana --transport http https://nanobanana.mcp.acedata.cloud/mcp \
-h "Authorization: Bearer YOUR_API_TOKEN"
```
Or add to your project's `.mcp.json`:
```json
{
"mcpServers": {
"nanobanana": {
"type": "streamable-http",
"url": "https://nanobanana.mcp.acedata.cloud/mcp",
"headers": {
"Authorization": "Bearer YOUR_API_TOKEN"
}
}
}
}
```
#### Cline
Add to Cline's MCP settings (`.cline/mcp_settings.json`):
```json
{
"mcpServers": {
"nanobanana": {
"type": "streamable-http",
"url": "https://nanobanana.mcp.acedata.cloud/mcp",
"headers": {
"Authorization": "Bearer YOUR_API_TOKEN"
}
}
}
}
```
#### Amazon Q Developer
Add to your MCP configuration:
```json
{
"mcpServers": {
"nanobanana": {
"type": "streamable-http",
"url": "https://nanobanana.mcp.acedata.cloud/mcp",
"headers": {
"Authorization": "Bearer YOUR_API_TOKEN"
}
}
}
}
```
#### Roo Code
Add to Roo Code MCP settings:
```json
{
"mcpServers": {
"nanobanana": {
"type": "streamable-http",
"url": "https://nanobanana.mcp.acedata.cloud/mcp",
"headers": {
"Authorization": "Bearer YOUR_API_TOKEN"
}
}
}
}
```
#### Continue.dev
Add to `.continue/config.yaml`:
```yaml
mcpServers:
- name: nanobanana
type: streamable-http
url: https://nanobanana.mcp.acedata.cloud/mcp
headers:
Authorization: "Bearer YOUR_API_TOKEN"
```
#### Zed
Add to Zed's settings (`~/.config/zed/settings.json`):
```json
{
"language_models": {
"mcp_servers": {
"nanobanana": {
"url": "https://nanobanana.mcp.acedata.cloud/mcp",
"headers": {
"Authorization": "Bearer YOUR_API_TOKEN"
}
}
}
}
}
```
#### cURL Test
```bash
# Health check (no auth required)
curl https://nanobanana.mcp.acedata.cloud/health
# MCP initialize
curl -X POST https://nanobanana.mcp.acedata.cloud/mcp \
-H "Content-Type: application/json" \
-H "Accept: application/json" \
-H "Authorization: Bearer YOUR_API_TOKEN" \
-d '{"jsonrpc":"2.0","id":1,"method":"initialize","params":{"protocolVersion":"2025-03-26","capabilities":{},"clientInfo":{"name":"test","version":"1.0"}}}'
```
### 3. Or Run Locally (Alternative)
If you prefer to run the server on your own machine:
```bash
# Install from PyPI
pip install mcp-nanobanana-pro
# or
uvx mcp-nanobanana-pro
# Set your API token
export ACEDATACLOUD_API_TOKEN="your_token_here"
# Run (stdio mode for Claude Desktop / local clients)
mcp-nanobanana-pro
# Run (HTTP mode for remote access)
mcp-nanobanana-pro --transport http --port 8000
```
#### Claude Desktop (Local)
```json
{
"mcpServers": {
"nanobanana": {
"command": "uvx",
"args": ["mcp-nanobanana-pro"],
"env": {
"ACEDATACLOUD_API_TOKEN": "your_token_here"
}
}
}
}
```
#### Docker (Self-Hosting)
```bash
docker pull ghcr.io/acedatacloud/mcp-nanobanana-pro:latest
docker run -p 8000:8000 ghcr.io/acedatacloud/mcp-nanobanana-pro:latest
```
Clients connect with their own Bearer token — the server extracts the token from each request's `Authorization` header.
## Available Tools
### Image Generation
| Tool | Description |
| --------------------------- | ------------------------------------ |
| `nanobanana_generate_image` | Generate an image from a text prompt |
| `nanobanana_edit_image` | Edit or combine images with AI |
### Tasks
| Tool | Description |
| ---------------------------- | ---------------------------- |
| `nanobanana_get_task` | Query a single task status |
| `nanobanana_get_tasks_batch` | 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 |
| ---------------------------- | --------------------------- | --------------------------- |
| `ACEDATACLOUD_API_TOKEN` | API token from AceDataCloud | **Required** |
| `ACEDATACLOUD_API_BASE_URL` | API base URL | `https://api.acedata.cloud` |
| `ACEDATACLOUD_OAUTH_CLIENT_ID` | OAuth client ID (hosted mode) | — |
| `ACEDATACLOUD_PLATFORM_BASE_URL` | Platform base URL | `https://platform.acedata.cloud` |
| `NANOBANANA_REQUEST_TIMEOUT` | Request timeout in seconds | `1800` |
| `LOG_LEVEL` | Logging level | `INFO` |
### Command Line Options
```bash
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
```bash
# Clone repository
git clone https://github.com/AceDataCloud/NanoBananaMCP.git
cd NanoBananaMCP
# 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
```bash
# Run unit tests
pytest
# Run with coverage
pytest --cov=core --cov=tools
# Run integration tests (requires API token)
pytest tests/test_integration.py -m integration
```
### Code Quality
```bash
# Format code
ruff format .
# Lint code
ruff check .
# Type check
mypy core tools
```
### Build & Publish
```bash
# 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
├── deploy/ # Deployment configs
│ └── production/
│ ├── deployment.yaml
│ ├── ingress.yaml
│ └── service.yaml
├── .env.example # Environment template
├── .gitignore
├── Dockerfile # Docker image for HTTP mode
├── docker-compose.yaml # Docker Compose config
├── LICENSE
├── main.py # Entry point
├── pyproject.toml # Project configuration
└── README.md
```
## API Reference
This server wraps the [AceDataCloud NanoBanana API](https://platform.acedata.cloud/documents/nano-banana-images):
- [NanoBanana Images API](https://platform.acedata.cloud/documents/nano-banana-images) - Image generation and editing
- [NanoBanana Tasks API](https://platform.acedata.cloud/documents/nano-banana-tasks) - 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:
1. Fork the repository
2. Create a feature branch (`git checkout -b feature/amazing`)
3. Commit your changes (`git commit -m 'Add amazing feature'`)
4. Push to the branch (`git push origin feature/amazing`)
5. Open a Pull Request
## Documentation
<!-- canonical-documentation -->
[Documentation](https://platform.acedata.cloud/documents/nano-banana-mcp)
## License
MIT License - see [LICENSE](LICENSE) for details.
## Links
- [AceDataCloud Platform](https://platform.acedata.cloud)
- [Model Context Protocol](https://modelcontextprotocol.io)
- [MCP Python SDK](https://github.com/modelcontextprotocol/python-sdk)
---
Made with love by [AceDataCloud](https://platform.acedata.cloud)