img-gen

# img-gen An MCP (Model Context Protocol) server that provides image generation and weather services for Claude Desktop and other MCP-compatible clients. ## Features ### 🎨 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 ### 🌤️ 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](https://github.com/astral-sh/uv) package manager - Google Gemini API key (for image generation) - Claude Desktop (optional, for MCP integration) ## Installation 1. Clone this repository: ```bash git clone <repository-url> cd img_gen ``` 2. Install dependencies using `uv`: ```bash 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`: ```python 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: ```json { "mcpServers": { "image_generation": { "command": "/path/to/uv", "args": [ "--directory", "/path/to/img_gen", "run", "image_generation.py" ] } } } ``` #### Weather Server Configuration: ```json { "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: ```bash uv run image_generation.py ``` #### Weather Server: ```bash 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/ ├── image_generation.py # MCP server for image generation using Gemini API ├── weather.py # MCP server for weather alerts and forecasts ├── main.py # Basic entry point ├── pyproject.toml # Project dependencies and configuration ├── uv.lock # Locked dependency versions └── 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 framework - `google-genai` - Google Gemini API client - `pillow` - Image processing - `httpx` - 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]