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Materials MCP

Materials MCP

Public
ZuchGuillotine/MatMCP

Model Context Protocol server enabling standardized access to materials databases via the OPTIMADE API, featuring efficient querying and retrieval of predicted stable crystal structures from Google DeepMind's GNoME dataset for advanced materials science applications.

python
0 tools
May 29, 2025
Updated Jun 4, 2025

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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]
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