Materials Project
Enables AI models to query and retrieve comprehensive materials science data from the Materials Project database via a Model Context Protocol server.
Acerca de
This tool provides a Model Context Protocol (MCP) server designed to bridge AI models with the vast Materials Project database. It allows large language models, like those integrated into Claude Desktop and VS Code Copilot, to access and interpret complex materials data, including crystal structures, electronic properties, and thermodynamic stability. By serving as an intermediary, it empowers AI assistants to become knowledgeable resources for materials science research, enabling them to answer queries and provide detailed information directly from the Materials Project's extensive collection.
Características Principales
- Search materials by elements, band gap range, and stability
- Retrieve crystal structures and lattice parameters by ID
- Obtain and plot electronic and phonon band structures
- Access magnetic properties, charge density, and dielectric data
- Compute thermodynamic stability, cohesive energies, and elastic constants
- 2 GitHub stars
Casos de Uso
- Enhancing developer environments (e.g., VS Code Copilot) with direct access to Materials Project data for coding and research.
- Enabling AI-driven queries and analysis for materials discovery and research workflows.
- Integrating materials science database search capabilities into AI chat applications like Claude Desktop.
