What is Gemini Mcp Server

Gemini MCP Server is a Model Context Protocol (MCP) server that allows Claude Desktop to generate images using Google’s Gemini AI models.

Use cases

Use cases include generating artwork based on specific prompts, creating illustrations for stories or presentations, and producing images for marketing materials or social media content.

How to use

To use Gemini MCP Server, install it via npm, run the setup wizard to configure your Google Gemini API key and output directory, and then restart Claude Desktop. You can then prompt Claude to generate images based on your requests.

Key features

Key features include direct image generation from Claude Desktop using Google’s Gemini models, an easy setup wizard, customizable image generation parameters, integration with Claude Desktop’s MCP server system, and detailed logging and debugging capabilities.

Where to use

Gemini MCP Server is primarily used in creative fields such as digital art, graphic design, and any application requiring AI-generated imagery.

Gemini MCP Server for Claude Desktop

A Model Context Protocol (MCP) server that enables Claude Desktop to generate images using Google’s Gemini AI models.

🌟 Features

• Generate images directly from Claude Desktop using Google’s Gemini models
• Easy setup wizard for configuration
• Customizable image generation parameters
• Integration with Claude Desktop’s MCP server system
• Detailed logging and debugging capabilities
• Docker support for easy deployment and sharing

📋 Requirements

• Node.js 16.x or higher
• Claude Desktop application
• Google Gemini API key (Get one here)
• Docker (optional, for containerized deployment)

🚀 Installation

Global Installation (Recommended)

npm install -g gemini-mcp-server

# Run the setup wizard
npx gemini-mcp-setup

Local Installation

# Create a directory for the server
mkdir gemini-mcp-server
cd gemini-mcp-server

# Install locally
npm install gemini-mcp-server

# Run the setup wizard
npx gemini-mcp-setup

Docker Installation

You can also run the Gemini MCP server using Docker:

# Build the Docker image
docker build -t gemini-mcp-server .

# Run the Docker container
docker run -e GEMINI_API_KEY="your-api-key" -e OUTPUT_DIR="/app/output" -v /path/on/host:/app/output gemini-mcp-server

⚙️ Setup

The setup wizard will guide you through the configuration process:

1. Enter your Google Gemini API key
2. Specify the directory for saving generated images
3. Configure logging and model settings
4. Automatically create a wrapper script for Claude Desktop
5. Update your Claude Desktop configuration

If you prefer manual setup, see the Manual Configuration section below.

🎨 Using the Gemini MCP Server

Once installed and configured, restart Claude Desktop to enable the Gemini MCP server. Then:

1. Start a conversation with Claude
2. Ask Claude to generate an image for you, for example:
   • “Generate an image of a mountain landscape at sunset”
   • “Create a picture of a futuristic city with flying cars”
   • “Make an illustration of a cat playing piano”

Claude will call the Gemini API to generate the image and provide you with the path to the saved image file.

Advanced Options

You can customize the image generation with additional parameters:

• Style: Specify a style like “realistic”, “artistic”, “minimalistic”, etc.
• Temperature: Control the creativity/randomness of the generation (0.0-1.0)

Example: “Generate an image of a cyberpunk city with neon lights in a realistic style with temperature 0.7”

🔧 Manual Configuration

If you prefer not to use the setup wizard, follow these steps:

1. Create Configuration File

Create a JSON configuration file with your settings:

{
  "apiKey": "YOUR_GEMINI_API_KEY_HERE",
  "outputDir": "/path/to/your/output/directory",
  "debug": true,
  "modelOptions": {
    "model": "gemini-2.0-flash-exp",
    "temperature": 0.4
  }
}

2. Create Wrapper Script

Create a bash script to run the server:

#!/bin/bash
# Set environment variables
export GEMINI_API_KEY="YOUR_GEMINI_API_KEY_HERE"
export OUTPUT_DIR="/path/to/your/output/directory"
export DEBUG="true"

# Execute the server
exec "$(which node)" "$(npm root -g)/gemini-mcp-server/bin/gemini-mcp-server.js"

Make the script executable:

chmod +x gemini-mcp-wrapper.sh

3. Update Claude Desktop Configuration

Edit your ~/.config/claude/claude_desktop_config.json file to add the Gemini MCP server:

{
  "mcpServers": {
    "gemini-image": {
      "command": "/bin/bash",
      "args": [
        "-c",
        "/path/to/your/gemini-mcp-wrapper.sh"
      ],
      "env": {
        "GEMINI_API_KEY": "YOUR_GEMINI_API_KEY_HERE",
        "DEBUG": "true"
      }
    }
  }
}

🐳 Docker Deployment

This MCP server includes a Dockerfile for easy deployment and sharing. The Docker image is configured to:

• Use Node.js 16 Alpine as a lightweight base
• Install all necessary dependencies
• Set up a default output directory at /app/output
• Allow configuration via environment variables

Building the Docker Image

docker build -t gemini-mcp-server .

Running with Docker

docker run \
  -e GEMINI_API_KEY="your-api-key" \
  -e OUTPUT_DIR="/app/output" \
  -e DEBUG="false" \
  -v /path/on/host:/app/output \
  gemini-mcp-server

Environment Variables for Docker

When running the Docker container, you can configure the server using these environment variables:

• GEMINI_API_KEY: Your Google Gemini API key (required)
• OUTPUT_DIR: Directory to save generated images (default: /app/output)
• DEBUG: Enable debug logging (default: false)

Using with Claude Desktop

When using the Docker container with Claude Desktop, you’ll need to:

1. Ensure the container is running
2. Configure Claude Desktop to connect to the containerized server
3. Map the output directory to a location accessible by Claude

📚 API Documentation

Command Line Interface

gemini-mcp-server [options]

Options:

• -k, --api-key <key>: Google Gemini API key
• -o, --output-dir <dir>: Directory to save generated images
• -d, --debug: Enable debug logging
• -c, --config <path>: Path to custom configuration file
• -r, --reset-config: Reset configuration to defaults
• -v, --version: Display version information

Environment Variables

• GEMINI_API_KEY: Your Google Gemini API key
• OUTPUT_DIR: Directory to save generated images
• DEBUG: Enable debug logging (true or false)
• LOG_LEVEL: Set log level (ERROR, WARN, INFO, or DEBUG)
• GEMINI_LOG_FILE: Custom log file path

Configuration Options

🔍 Troubleshooting

Common Issues

Server doesn’t start or Claude can’t connect to it

1. Check the log file at ~/Claude/logs/gemini-image-mcp.log
2. Verify your API key is correct
3. Ensure all directories exist and have proper permissions
4. Restart Claude Desktop

Images aren’t being generated

1. Verify your Google Gemini API key has the correct permissions
2. Check if the output directory exists and is writable
3. Examine the logs for specific error messages
4. Try a different prompt or model

Error: “Method not found”

This usually means Claude is trying to call a method that the MCP server doesn’t support. Check the logs to see what method was requested.

Docker-specific issues

1. Ensure the container has proper network connectivity
2. Check if volume mounts are correctly configured
3. Verify environment variables are properly set
4. Review container logs with docker logs [container-id]

Debug Mode

Enable debug mode for more detailed logs:

npx gemini-mcp-server --debug

Or set the environment variable:

export DEBUG=true
npx gemini-mcp-server

📝 License

MIT

🙏 Acknowledgements

• Model Context Protocol for the MCP specification
• Google Generative AI for the Gemini API
• All contributors to this project