mcp-vision-recognition

# MCP Image Recognition Server An MCP server that provides image recognition capabilities using Anthropic and OpenAI vision APIs. Version 0.1.2. ## Features - Image description using Anthropic Claude Vision or OpenAI GPT-4 Vision - Support for multiple image formats (JPEG, PNG, GIF, WebP) - Configurable primary and fallback providers - Base64 and file-based image input support - Optional text extraction using Tesseract OCR ## Requirements - Python 3.8 or higher - Tesseract OCR (optional) - Required for text extraction feature - Windows: Download and install from [UB-Mannheim/tesseract](https://github.com/UB-Mannheim/tesseract/wiki) - Linux: `sudo apt-get install tesseract-ocr` - macOS: `brew install tesseract` ## Installation 1. Clone the repository: ```bash git clone https://github.com/mario-andreschak/mcp-image-recognition.git cd mcp-image-recognition ``` 2. Create and configure your environment file: ```bash cp .env.example .env # Edit .env with your API keys and preferences ``` 3. Build the project: ```bash build.bat ``` ## Usage ### Running the Server Spawn the server using python: ```bash python -m mcp_vision_recognition.server ``` Start the server using batch instead: ```bash run.bat server ``` Start the server in development mode with the MCP Inspector: ```bash run.bat debug ``` ### Available Tools 1. `describe_image` - Input: Base64-encoded image data and MIME type - Output: Detailed description of the image 2. `describe_image_from_file` - Input: Path to an image file - Output: Detailed description of the image ### Environment Configuration - `ANTHROPIC_API_KEY`: Your Anthropic API key. - `OPENAI_API_KEY`: Your OpenAI API key. - `VISION_PROVIDER`: Primary vision provider (`anthropic` or `openai`). - `FALLBACK_PROVIDER`: Optional fallback provider. - `LOG_LEVEL`: Logging level (DEBUG, INFO, WARNING, ERROR). - `MAX_TOKENS`: Maximum number of tokens generated in a vision response (default: `1024`). - `ENABLE_OCR`: Enable Te…