MatMCP

ZuchGuillotine/MatMCP

3.1

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The Materials MCP Project is a server designed to interface with materials databases via the OPTIMADE API, focusing on the GNoME dataset for crystal structure data.

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: 
    python -m venv venv
source venv/bin/activate  # On Unix/macOS
  3. Install dependencies using Poetry: 
    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]