gemini-gen-mcp 0.0.1

MCP Server for Gemini Image and Audio generation

Gemini Gen MCP

MCP Server for Gemini Image and Audio generation using Google's Gemini AI models.

Features

This MCP server provides tools to:

• Generate images from text using Gemini's Flash Image model
• Generate audio from text using Gemini 2.5 Flash Preview TTS model

Installation

From PyPI

pip install gemini-gen-mcp

From Source

git clone https://github.com/ServiceStack/gemini-gen-mcp.git
cd gemini-gen-mcp
pip install -e .

Prerequisites

You need a Google Gemini API key to use this server. Get one from Google AI Studio.

Environment Variables

Variable	Required	Default	Description
GEMINI_API_KEY	Yes	-	Your Google Gemini API key
GEMINI_DOWNLOAD_PATH	No	/tmp/gemini_gen_mcp	Directory where generated files are saved

Set the environment variables:

export GEMINI_API_KEY='your-api-key-here'
export GEMINI_DOWNLOAD_PATH='/path/to/downloads'  # optional

Generated files are organized by type and date:

• Images: $GEMINI_DOWNLOAD_PATH/images/YYYY-MM-DD/
• Audio: $GEMINI_DOWNLOAD_PATH/audios/YYYY-MM-DD/

Each generated file includes a companion .info.json file with generation metadata.

Usage

Running the Server

Run the MCP server directly:

gemini-gen-mcp

Or as a Python module:

python -m gemini_gen_mcp.server

Using with Claude Desktop

See CLAUDE_CONFIG.md for detailed instructions.

Add this to your claude_desktop_config.json:

{
  "mcpServers": {
    "gemini-gen": {
      "command": "gemini-gen-mcp",
      "env": {
        "GEMINI_API_KEY": "your-api-key-here"
      }
    }
  }
}

Available Tools

text_to_image

Generate images from text descriptions using Gemini's image generation models.

Parameters:

• prompt (string, required): Text description of the image to generate
• model (string, optional): Gemini model to use
  • gemini-2.5-flash-image (default)
  • gemini-3-pro-image-preview
• aspect_ratio (string, optional): Aspect ratio for the generated image (default: "1:1")
  • Supported: 1:1, 2:3, 3:2, 3:4, 4:3, 4:5, 5:4, 9:16, 16:9, 21:9
• temperature (float, optional): Sampling temperature for image generation (default: 1.0)
• top_p (float, optional): Nucleus sampling parameter (optional)

Example:

{
  "prompt": "A serene mountain landscape at sunset with a lake",
  "model": "gemini-2.5-flash-image",
  "aspect_ratio": "16:9",
  "temperature": 1.0
}

text_to_audio

Generate audio/speech from text using Gemini's TTS models. Output is saved as WAV format.

Parameters:

• text (string, required): Text to convert to speech
• model (string, optional): Gemini TTS model to use
  • gemini-2.5-flash-preview-tts (default)
  • gemini-2.5-pro-preview-tts
• voice (string, optional): Voice to use for speech generation (default: "Kore")

Available Voices:

Voice	Style	Voice	Style	Voice	Style
Zephyr	Bright	Puck	Upbeat	Charon	Informative
Kore	Firm	Fenrir	Excitable	Leda	Youthful
Orus	Firm	Aoede	Breezy	Callirrhoe	Easy-going
Autonoe	Bright	Enceladus	Breathy	Iapetus	Clear
Umbriel	Easy-going	Algieba	Smooth	Despina	Smooth
Erinome	Clear	Algenib	Gravelly	Rasalgethi	Informative
Laomedeia	Upbeat	Achernar	Soft	Alnilam	Firm
Schedar	Even	Gacrux	Mature	Pulcherrima	Forward
Achird	Friendly	Zubenelgenubi	Casual	Vindemiatrix	Gentle
Sadachbia	Lively	Sadaltager	Knowledgeable	Sulafat	Warm

Example:

{
  "text": "Hello, this is a test of the Gemini text to speech system.",
  "model": "gemini-2.5-flash-preview-tts",
  "voice": "Kore"
}

Development

Setup Development Environment

# Clone the repository
git clone https://github.com/ServiceStack/gemini-gen-mcp.git
cd gemini-gen-mcp

# Install in editable mode with dependencies
pip install -e .

Running Tests

# Install test dependencies
pip install pytest pytest-asyncio

# Run tests
```bash
# uv run pytest tests -v
npm test

License

This project is licensed under the MIT License - see the LICENSE file for details.

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

Support

For issues and questions, please use the GitHub Issues page.

Acknowledgments

• Built with FastMCP
• Powered by Google Gemini AI

Links

• PyPI Package
• GitHub Repository
• Google AI Studio
• MCP Documentation