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MCP LAMMPS Server
- python
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GitHub Stars
python
Language
6 months ago
First Indexed
2 months ago
Catalog Refreshed
Documentation & install
Readme and setup notes from the catalogue, plus a client-ready config you can copy for your MCP host.
Installation
Add the following to your MCP client configuration file.
Configuration
View docs{
"mcpServers": {
"chenghao-wu-mcp_lammps": {
"command": "python",
"args": [
"-m",
"mcp_lammps.server"
],
"env": {
"MCP_LAMMPS_WORK_DIR": "/path/to/workspace",
"MCP_LAMMPS_LOG_LEVEL": "INFO"
}
}
}
}You can run an MCP LAMMPS Server to manage and automate molecular dynamics simulations using LAMMPS. This server provides a standardized interface so you can configure, execute, monitor, and analyze simulations through simple prompts, making it easier to integrate AI-driven workflows into your computational materials work.
How to use
You will interact with the MCP LAMMPS Server through an MCP client. Start the server, then issue natural language prompts to set up simulations, run equilibration and production phases, monitor progress in real time, and fetch results for analysis. You can define multi-step workflows that automate setup, execution, and post-processing without manually editing input files.
How to install
Follow these steps to install and run the MCP LAMMPS Server on your machine.
# Prerequisites
# Ensure you have Python 3.9 or higher
# Install LAMMPS with Python interface (as required by your setup)
# Install RDKit for molecular processing
# Install Packmol for organic liquid box creation
# Clone the MCP LAMMPS repository
git clone https://github.com/mcp-lammps/mcp-lammps.git
cd mcp-lammps
# Create and activate a virtual environment
python -m venv venv
source venv/bin/activate # On Windows: venv\Scripts\activate
# Install Python dependencies
pip install -r requirements.txt
# Install in development mode
pip install -e .
# Run the MCP LAMMPS server
python -m mcp_lammps.server
Additional setup and runtime notes
The server supports configuration via environment variables. You can adjust logging and working directory to fit your environment.
export MCP_LAMMPS_LOG_LEVEL=INFO
export MCP_LAMMPS_WORK_DIR=/path/to/workspace
python -m mcp_lammps.server
Available tools
setup_tools
Tools to configure and prepare simulations, including SMILES processing and initial structure generation.
control_tools
Tools to manage simulation lifecycles, including starting, pausing, resuming, and stopping runs.
analysis_tools
Tools to analyze trajectories and compute properties from MD simulations.
monitoring_tools
Real-time monitoring tools to track progress and key system properties.
organic_tools
Specialized tools for handling organic molecules and GAFF-based workflows.