img-gen
Provides tools for generating optimized images via Google's Gemini model and fetching weather forecasts and alerts from the National Weather Service. It enables users to create visual content and retrieve environmental data seamlessly within MCP-compatible clients.
README
img-gen
An MCP (Model Context Protocol) server that provides image generation and weather services for Claude Desktop and other MCP-compatible clients.
Features
šØ Image Generation
- Generate images using Google's Gemini 2.5 Flash Image model
- Automatic image compression and resizing to optimize token usage
- Base64 encoding for seamless integration with MCP clients
- Comprehensive logging and error handling
š¤ļø Weather Services
- Get weather alerts for US states
- Fetch detailed weather forecasts by latitude/longitude
- Uses the National Weather Service (NWS) API
Prerequisites
- Python 3.11 or higher
- uv package manager
- Google Gemini API key (for image generation)
- Claude Desktop (optional, for MCP integration)
Installation
- Clone this repository:
git clone <repository-url>
cd img_gen
- Install dependencies using
uv:
uv sync
Configuration
Google Gemini API Key
For image generation, you need to set up your Google Gemini API key. Update the API_KEY variable in image_generation.py:
API_KEY = "your-api-key-here"
Alternatively, you can modify the code to read from an environment variable for better security.
Claude Desktop Integration
To use this MCP server with Claude Desktop, add the following configuration to your Claude Desktop config file:
macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
Windows: %APPDATA%\Claude\claude_desktop_config.json
Linux: ~/.config/Claude/claude_desktop_config.json
Image Generation Server Configuration:
{
"mcpServers": {
"image_generation": {
"command": "/path/to/uv",
"args": [
"--directory",
"/path/to/img_gen",
"run",
"image_generation.py"
]
}
}
}
Weather Server Configuration:
{
"mcpServers": {
"weather": {
"command": "/path/to/uv",
"args": [
"--directory",
"/path/to/img_gen",
"run",
"weather.py"
]
}
}
}
Note: Replace /path/to/uv with your actual uv installation path (e.g., /Users/username/.local/bin/uv) and /path/to/img_gen with the absolute path to this project directory.
Usage
Running the MCP Servers
Image Generation Server:
uv run image_generation.py
Weather Server:
uv run weather.py
Image Generation
The generate_image tool accepts a text prompt and returns a generated image:
- Tool:
generate_image - Parameters:
prompt(string): A text description of the image you want to generate
- Returns: MCP Content objects containing the generated image in base64 format
Weather Services
Get Weather Alerts
- Tool:
get_alerts - Parameters:
state(string): Two-letter US state code (e.g., "CA", "NY")
- Returns: Active weather alerts for the specified state
Get Weather Forecast
- Tool:
get_forecast - Parameters:
latitude(float): Latitude of the location (up to 4 decimal places recommended)longitude(float): Longitude of the location (up to 4 decimal places recommended)
- Returns: Detailed weather forecast for the next 5 periods
Project Structure
img_gen/
āāā image_generation.py # MCP server for image generation using Gemini API
āāā weather.py # MCP server for weather alerts and forecasts
āāā main.py # Basic entry point
āāā pyproject.toml # Project dependencies and configuration
āāā uv.lock # Locked dependency versions
āāā README.md # This file
Image Processing
The image generation server includes automatic image optimization:
- Max Dimension: 1024 pixels (maintains aspect ratio)
- JPEG Quality: 85
- Target File Size: ~500 KB
- Format: Converts all images to JPEG for consistency
Images are automatically resized and compressed to reduce token usage while maintaining reasonable quality.
Dependencies
Key dependencies include:
mcp[cli]- Model Context Protocol frameworkgoogle-genai- Google Gemini API clientpillow- Image processinghttpx- HTTP client for weather API
See pyproject.toml for the complete list of dependencies.
Logging
Both servers include comprehensive logging:
- Logs are written to
stderr - Log levels: INFO, DEBUG, WARNING, ERROR
- Includes timestamps and module names
Error Handling
- Image generation failures return error messages via MCP
- Weather API failures gracefully handle network issues
- Invalid inputs are validated and return appropriate error messages
License
[Add your license here]
Contributing
[Add contribution guidelines if applicable]
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