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mcp-atomictoolkit

MCP.Pizza Chef: XirtamEsrevni

The mcp-atomictoolkit is an MCP-compatible server that enables atomistic simulation workflows using ASE, pymatgen, and machine learning interatomic potentials. It supports structure creation, manipulation, geometry optimization, and file I/O operations, facilitating advanced materials modeling and computational chemistry tasks within MCP-enabled environments.

Use This MCP server To

Create and manipulate atomic structures programmatically Perform geometry optimizations on molecular and crystal structures Read and write atomic structure files in various formats Integrate machine learning interatomic potentials for simulations Automate atomistic simulation workflows in MCP-enabled apps Enable real-time interaction with materials modeling tools Support computational chemistry tasks within AI workflows

README

Atomistic Toolkit MCP Server

Note

This project is under active development. Not everything is working yet.

An MCP-compatible server providing atomistic simulation capabilities through ASE, pymatgen, and machine learning interatomic potentials (MLIPs).

Features

ASE Tools

  • Structure creation and manipulation
  • Geometry optimization
  • File I/O operations (read/write structures)

mcp-atomictoolkit FAQ

How do I integrate mcp-atomictoolkit with my MCP client?
Connect your MCP client to the mcp-atomictoolkit server endpoint and use the defined MCP protocol commands to access atomistic simulation features.
What simulation tools does mcp-atomictoolkit support?
It supports ASE for atomic simulations, pymatgen for materials analysis, and machine learning interatomic potentials for advanced modeling.
Can mcp-atomictoolkit handle file input/output for atomic structures?
Yes, it supports reading and writing various atomic structure file formats to facilitate data exchange.
Is mcp-atomictoolkit suitable for real-time simulation workflows?
Yes, it is designed to enable real-time interaction with atomistic simulation tools within MCP environments.
What programming languages or environments is mcp-atomictoolkit compatible with?
It is accessible via MCP protocol, making it compatible with any MCP client regardless of programming language, including Python, JavaScript, and others.
Does mcp-atomictoolkit support machine learning potentials?
Yes, it integrates machine learning interatomic potentials to enhance simulation accuracy and efficiency.
Is mcp-atomictoolkit production-ready?
The project is under active development, so some features may be incomplete or experimental.