Materials MCP

# Materials MCP Project A Model Context Protocol (MCP) server designed to interact with materials databases through the OPTIMADE API, with a specific focus on Google DeepMind's GNoME (Graph Networks for Materials Exploration) dataset. This project serves as a bridge between the OPTIMADE API and materials science applications, enabling efficient access and manipulation of crystal structure data. ## Overview The Materials MCP Project implements a Model Context Protocol server that: - Interfaces with the OPTIMADE API to access materials databases - Provides specialized access to the GNoME dataset, which contains millions of predicted stable crystal structures - Enables efficient querying and retrieval of crystal structures and their properties - Supports standardized data exchange formats for materials science applications ## Features - OPTIMADE API integration for standardized materials database access - GNoME dataset integration for accessing predicted stable crystal structures - RESTful API endpoints for crystal structure queries - Support for common materials science data formats - Efficient data caching and retrieval mechanisms - Standardized query language support ## Setup 1. Ensure you have Python 3.10 or higher installed 2. Create a virtual environment: ```bash python -m venv venv source venv/bin/activate # On Unix/macOS ``` 3. Install dependencies using Poetry: ```bash pip install poetry poetry install ``` ## Project Structure - `materials_mcp/` - Main package directory - `api/` - OPTIMADE API integration - `gnome/` - GNoME dataset specific functionality - `models/` - Data models and schemas - `server/` - MCP server implementation - `tests/` - Test directory - `pyproject.toml` - Project configuration and dependencies - `README.md` - This file ## Dependencies - Python >=3.10 - optimade >=1.2.4 - For OPTIMADE API integration - Additional dependencies will be added as needed for: - FastAPI/Flask for the web server - Database integration - Data processing and analysis - Testing and documentation ## Usage [Usage examples will be added as the project develops] ## Contributing [Contribution guidelines will be added] ## License [License information will be added] ## Acknowledgments - Google DeepMind for the GNoME dataset - OPTIMADE consortium for the API specification - [Other acknowledgments to be added]