Provides image generation capabilities using Google's Gemini AI models with customizable parameters like style and temperature
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)
Local Installation
Docker Installation
You can also run the Gemini MCP server using Docker:
⚙️ Setup
The setup wizard will guide you through the configuration process:
Enter your Google Gemini API key
Specify the directory for saving generated images
Configure logging and model settings
Automatically create a wrapper script for Claude Desktop
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:
Start a conversation with Claude
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:
2. Create Wrapper Script
Create a bash script to run the server:
Make the script executable:
3. Update Claude Desktop Configuration
Edit your ~/.config/claude/claude_desktop_config.json
file to add the Gemini MCP server:
🐳 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
Running with Docker
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:
Ensure the container is running
Configure Claude Desktop to connect to the containerized server
Map the output directory to a location accessible by Claude
📚 API Documentation
Command Line Interface
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 keyOUTPUT_DIR
: Directory to save generated imagesDEBUG
: Enable debug logging (true
orfalse
)LOG_LEVEL
: Set log level (ERROR
,WARN
,INFO
, orDEBUG
)GEMINI_LOG_FILE
: Custom log file path
Configuration Options
Option | Description | Default |
| Google Gemini API key | (required) |
| Directory to save generated images |
|
| Enable debug logging |
|
| Gemini model to use |
|
| Control creativity/randomness |
|
| Top-k sampling parameter |
|
| Top-p sampling parameter |
|
| Maximum output tokens |
|
🔍 Troubleshooting
Common Issues
Server doesn't start or Claude can't connect to it
Check the log file at
~/Claude/logs/gemini-image-mcp.log
Verify your API key is correct
Ensure all directories exist and have proper permissions
Restart Claude Desktop
Images aren't being generated
Verify your Google Gemini API key has the correct permissions
Check if the output directory exists and is writable
Examine the logs for specific error messages
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
Ensure the container has proper network connectivity
Check if volume mounts are correctly configured
Verify environment variables are properly set
Review container logs with
docker logs [container-id]
Debug Mode
Enable debug mode for more detailed logs:
Or set the environment variable:
📝 License
MIT
🙏 Acknowledgements
Model Context Protocol for the MCP specification
Google Generative AI for the Gemini API
All contributors to this project
hybrid server
The server is able to function both locally and remotely, depending on the configuration or use case.
Tools
A server that enables Claude Desktop to generate images using Google's Gemini AI models through the Model Context Protocol (MCP).
Related MCP Servers
- -securityAlicense-qualityModel Context Protocol (MCP) server implementation that enables Claude Desktop to interact with Google's Gemini AI models.Last updated -226MIT License
- -security-license-qualityAn MCP server implementation that allows using Google's Gemini AI models (specifically Gemini 1.5 Pro) through Claude or other MCP clients via the Model Context Protocol.Last updated -1
- -securityFlicense-qualityA Model Context Protocol server that enables Claude Desktop to interact with Google's Gemini 2.5 Pro Experimental AI model, with features like Google Search integration and token usage reporting.Last updated -3
- -securityAlicense-qualityAn MCP server that enables other AI models (like Claude) to use Google's Gemini models as tools for specific tasks through a standardized interface.