What is Openmm Mcp Server

openmm-mcp-server is an open-source platform designed for molecular dynamics (MD) simulations, providing a structured communication interface for task submission, management, and execution, integrated with OpenMM and DFT calculations via the Abacus engine.

Use cases

Use cases for openmm-mcp-server include simulating protein dynamics, analyzing membrane systems, performing DFT calculations for material properties, and conducting advanced sampling methods for free energy calculations.

How to use

To use openmm-mcp-server, clone the repository, install the necessary dependencies, optionally install OpenMM for simulations, and configure your MCP settings to integrate with your code. You can then run the server and submit tasks using simple commands.

Key features

Key features include complete OpenMM integration, DFT calculations with Abacus, pre-configured templates for various simulations, advanced sampling techniques, GPU acceleration support, asynchronous task management, and a natural language interface for user interaction.

Where to use

openmm-mcp-server is primarily used in the fields of computational chemistry, molecular biology, and materials science, where molecular dynamics simulations and quantum mechanical calculations are essential.

OpenMM MCP Server

English | 中文

🧬 OpenMM & Abacus MCP Server

A comprehensive Model Context Protocol (MCP) server for molecular dynamics simulations using OpenMM and DFT calculations with Abacus. This server provides a natural language interface for complex molecular simulations through LLM integration.

✨ Features

• Complete OpenMM Integration: Support for all OpenMM features including advanced integrators, barostats, and constraints
• DFT Calculations: Abacus DFT engine integration for quantum mechanical calculations
• Pre-configured Templates: Ready-to-use setups for protein simulations, membrane systems, and more
• Advanced Sampling: Metadynamics, free energy calculations, and enhanced sampling methods
• GPU Acceleration: CUDA and OpenCL platform support for high-performance computing
• Task Management: Asynchronous task execution with persistence and monitoring
• Natural Language Interface: Interact with complex simulations using simple English commands

🚀 Quick Start

Installation

# Clone the repository
git clone <repository_url>
cd openmm-mcp-server

# Install dependencies
pip install -r requirements.txt

# Optional: Install OpenMM for actual simulations
conda install -c conda-forge openmm

# Test installation
python test_mcp_server.py

Roo Code Integration

Add to your Code/Cline/Claude MCP settings:

{
  "mcpServers": {
    "openmm-server": {
      "command": "python",
      "args": [
        "run_openmm_server.py"
      ],
      "cwd": "path-to\\openmm-mcp-server",
      "alwaysAllow": [
        "create_md_simulation",
        "create_advanced_md_simulation",
        "setup_protein_simulation",
        "setup_membrane_simulation",
        "create_dft_calculation",
        "control_simulation",
        "get_task_status",
        "list_all_tasks",
        "analyze_results"
      ]
    }
  }
}

Important: Replace the path with your actual project path!

🛠️ Available Tools

Basic Tools

• create_md_simulation - Create simple MD simulations
• create_dft_calculation - Create DFT calculations
• control_simulation - Control simulation execution (start/stop/pause)
• get_task_status - Check task status
• list_all_tasks - List all tasks
• analyze_results - Analyze simulation results

Advanced Tools

• create_advanced_md_simulation - Full OpenMM feature support (50+ parameters)
• setup_protein_simulation - Pre-configured protein simulation templates
• setup_membrane_simulation - Membrane protein simulation setup

💬 Usage Examples

Simple Water Simulation

"Run a molecular dynamics simulation of a water molecule at 300K for 10000 steps"

Advanced Protein Simulation

"Set up a protein production simulation for 100 nanoseconds at physiological temperature 310K, using Amber19 force field with TIP3P-FB water model, 0.15M salt concentration, and GPU acceleration"

Membrane Protein Simulation

"Create a POPC membrane protein simulation for 50 nanoseconds with surface tension control"

📊 OpenMM Parameters Reference

Integrators

• LangevinMiddle - Langevin middle integrator (recommended)
• Verlet - Verlet integrator (NVE ensemble)
• Brownian - Brownian dynamics
• VariableLangevin - Variable step size Langevin
• VariableVerlet - Variable step size Verlet
• NoseHoover - Nose-Hoover thermostat

Force Fields

• Amber14: ["amber14-all.xml", "amber14/tip3pfb.xml"]
• Amber19: ["amber19-all.xml", "amber19/tip3pfb.xml"]
• CHARMM36: ["charmm36_2024.xml", "charmm36/water.xml"]

Water Models

• tip3p - TIP3P water model
• tip3pfb - TIP3P-FB water model (recommended)
• tip4pew - TIP4P-Ew water model
• spce - SPC/E water model

Platforms

• CUDA - NVIDIA GPU (fastest)
• OpenCL - General GPU
• CPU - CPU computation
• Reference - Reference implementation

Nonbonded Methods

• PME - Particle Mesh Ewald (recommended for periodic systems)
• NoCutoff - No cutoff (small systems)
• CutoffNonPeriodic - Non-periodic cutoff
• CutoffPeriodic - Periodic cutoff
• Ewald - Traditional Ewald summation

Constraints

• None - No constraints
• HBonds - Hydrogen bond constraints (recommended)
• AllBonds - All bond constraints
• HAngles - Hydrogen angle constraints

Barostats

• MonteCarloBarostat - Isotropic pressure control
• MonteCarloAnisotropicBarostat - Anisotropic pressure control
• MonteCarloMembraneBarostat - Membrane system pressure control

Precision

• mixed - Mixed precision (recommended)
• single - Single precision
• double - Double precision

🔧 Configuration

Environment variables:

export TASK_DATA_DIR="./simulation_data"
export MAX_CONCURRENT_TASKS=4
export DEFAULT_OPENMM_PLATFORM="CUDA"
export LOG_LEVEL="INFO"
export LOG_FILE="./mcp_server.log"

📁 Project Structure

openmm-mcp-server/
├── run_openmm_server.py      # Startup script
├── test_mcp_server.py        # Test script
├── requirements.txt          # Dependencies
├── README.md                 # English documentation
├── README_CN.md              # Chinese documentation
├── src/
│   ├── server_new.py         # Main server
│   ├── advanced_md_tools.py  # Advanced MD tools
│   ├── task_manager.py       # Task management
│   ├── openmm_engine.py      # OpenMM engine
│   ├── abacus_engine.py      # Abacus DFT engine
│   ├── config.py             # Configuration management
│   ├── tools/                # MCP tool implementations
│   ├── resources/            # MCP resource implementations
│   └── utils/                # Utility functions
├── tests/                    # Test files
├── examples/                 # Example code
├── docs/                     # Documentation
└── task_data/                # Task data directory (auto-created)

📚 Additional Documentation

• Installation Guide - Detailed installation instructions
• Usage Guide - Comprehensive usage examples
• Roo Code Integration - Detailed integration guide
• OpenMM Parameters - Complete parameter reference
• Project Analysis - Technical analysis and improvements

🔍 Troubleshooting

Common Issues

1. “OpenMM not found” warning

   • This is normal, server will run in mock mode
   • For actual simulations, install OpenMM: conda install -c conda-forge openmm

2. “command not found” error

   • Check if Python is in PATH
   • Verify project path is correct
   • Try using absolute paths

3. Permission errors

   • Ensure read/write permissions for project directory
   • Check if task_data directory is writable

Verify Configuration

# Test server startup
python run_openmm_server.py

# Test MCP functionality
python test_mcp_server.py

🤝 Contributing

1. Fork the repository
2. Create a feature branch
3. Make your changes
4. Add tests
5. Submit a pull request

🆘 Support

If you encounter any issues:

1. Run the test script: python test_mcp_server.py
2. Review the documentation
3. Check log files (if configured)
4. Submit an issue on GitHub

📄 License

This project is licensed under the GNU General Public License v3.0.

Happy simulating! 🎉