io.github.AceDataCloud/mcp-nanobanana-pro — MCP Server

MCP server for NanoBanana AI image generation and editing. Published as mcp-nanobanana-pro on PyPI and labeled as Python 3.10+ compatible. Licensed under MIT.

🛠️ Key Features

MCP server for NanoBanana AI image generation and editing
Topics: ai-image, image-editing, image-generation, mcp-server, model-context-protocol, developer-tools

🚀 Use Cases

Generate images with NanoBanana AI
Edit existing images using NanoBanana AI

⚡ Developer Benefits

MCP-Compatible for Model Context Protocol integration
Uses Python 3.10+ requirements
MIT license

⚠️ Limitations

No further tool or capability details are provided in the available excerpt (e.g., tool count or specific operations).

NanoBananaMCP

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

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

Sign up at AceDataCloud Platform
Go to the API documentation page
Click "Acquire" to get your API token
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 with OAuth — no API token needed:

Go to Claude.ai Settings → Integrations → Add More
Enter the server URL: https://nanobanana.mcp.acedata.cloud/mcp
Complete the OAuth login flow
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 for VS Code, which registers the hosted MCP servers with one-click setup.

JetBrains IDEs

Go to Settings → Tools → AI Assistant → Model Context Protocol (MCP)
Click Add → HTTP
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

code

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

code

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

code

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

code

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

code

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:

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

io.github.AceDataCloud/mcp-nanobanana-pro — MCP Server

🛠️ Key Features

🚀 Use Cases

⚡ Developer Benefits

⚠️ Limitations

Topics

NanoBananaMCP

Features

Tool Reference

Quick Start

1. Get Your API Token

2. Use the Hosted Server (Recommended)

Claude.ai

Claude Desktop

Cursor / Windsurf

VS Code (Copilot)

JetBrains IDEs

Claude Code

Cline

Amazon Q Developer

Roo Code

Continue.dev

Zed

cURL Test

3. Or Run Locally (Alternative)

Claude Desktop (Local)

Docker (Self-Hosting)

Available Tools

Image Generation

Tasks

Usage Examples

Generate Image from Prompt

Virtual Try-On

Product Photography

Prompt Writing Tips

Example Prompt

Configuration

Environment Variables

Command Line Options

Development

Setup Development Environment

Run Tests

Code Quality

Build & Publish

Project Structure

API Reference

Use Cases

Contributing

Documentation

License

Links

Install

Configuration

Related servers