mcp-nano-banana 0.1.2

Um servidor MCP que gera imagens usando a Google Gemini API.

MCP Nano Banana

This project is an MCP (Model Context Protocol) server that generates images using the Google Gemini API.

Description

This server implements the Model Context Protocol to expose a single tool, generate_image, to a compatible AI model. The tool accepts a text prompt, uses the Google Gemini API to generate an image, saves the image to the public/ directory for auditing, and returns the raw image data as a base64-encoded string.

To use the server with Claude Desktop or other applications

You need a Google Gemini API key and ImgBB API key to use this server.

Access https://api.imgbb.com/ to generate a IMGBB API Key. This is used to store and host the image online.

{
  "mcpServers": {
    "mcp-nano-banana": {
        "command": "uvx",
        "args": [
            "mcp-nano-banana"
        ],
        "env": {
            "GEMINI_API_KEY": "YOUR_API_KEY_HERE",
            "IMGBB_API_KEY": "YOUR_API_KEY_HERE"
        }
    }
  }
}

Dev Setup

1. Dependencies

This project uses Python and its dependencies are defined in pyproject.toml. You can install them using pip:

pip install .

This will install mcp, google-generativeai, and other required packages.

2. API Key

You need a Google Gemini API key and ImgBB API key to use this server.

Access https://api.imgbb.com/ to generate a IMGBB API Key. This is used to store and host the image online.

1. Create a file named .env in the root of the project.
2. Add your API key to the .env file in the following format:

    GEMINI_API_KEY="YOUR_API_KEY_HERE"
    IMGBB_API_KEY="YOUR_API_KEY_HERE"

Running the Server

This server is designed to be run as a subprocess by an MCP client or using the mcp command-line tool. The server listens for requests on stdio.

uvx --from git+https://github.com/GuilhermeAumo/mcp-nano-banana mcp-nano-banana

Publishing new pipy version

To publish a new version of this package to PyPI:

1. Update the version
   Edit the version field in pyproject.toml to the new version number.

2. Build the package
   Run:

   python -m build
   

   This will create .tar.gz and .whl files in the dist/ directory.

3. Upload to PyPI
   Make sure you have twine installed:

   pip install twine
   

   Then upload:

   twine upload dist/*
   

4. Tag the release (optional but recommended)

   git tag v<new-version>
   git push --tags
   

Note:

• You need a PyPI account and must be listed as a maintainer of the project.
• For test uploads, use TestPyPI and replace the upload command with:

  twine upload --repository testpypi dist/*
  

For more details, see the Python Packaging User Guide.