scicomp-molecular-mcp
MCP server for classical molecular dynamics simulations.
Overview
This server provides tools for molecular dynamics simulations with support for various ensembles and interaction potentials:
- Particle systems - Create and manage systems of interacting particles
- Interaction potentials - Lennard-Jones and Coulomb interactions
- Ensembles - NVE (microcanonical), NVT (canonical), NPT (isothermal-isobaric)
- Analysis tools - Radial distribution functions, mean squared displacement, phase transitions
- Visualization - Trajectory rendering and density field visualization
- GPU acceleration - Optional CUDA acceleration for large systems
Installation & Usage
# Run directly with uvx (no installation required)
uvx scicomp-molecular-mcp
# Or install with pip
pip install scicomp-molecular-mcp
# With GPU support
pip install scicomp-molecular-mcp[gpu]
# Run as command
scicomp-molecular-mcp
Available Tools
System Setup
create_particles- Initialize particle system with temperatureadd_potential- Add Lennard-Jones or Coulomb interactions
Simulation
run_md- NVE ensemble (constant energy, volume)run_nvt- NVT ensemble (constant temperature, volume)run_npt- NPT ensemble (constant temperature, pressure)get_trajectory- Retrieve simulation trajectory data
Analysis
compute_rdf- Radial distribution function analysiscompute_msd- Mean squared displacementanalyze_temperature- Thermodynamic propertiesdetect_phase_transition- Identify phase transitionsdensity_field- Compute density field visualization
Visualization
render_trajectory- Animate particle trajectories
Configuration
Enable GPU acceleration with environment variable:
MCP_USE_GPU=1 scicomp-molecular-mcp
Examples
See the API documentation for detailed examples and simulation protocols.
Part of Math-Physics-ML MCP System
Part of a comprehensive system for scientific computing. See the documentation for the complete ecosystem.
Metadata
Release files for scicomp-molecular-mcp 0.1.2
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| scicomp_molecular_mcp-0.1.2.tar.gz | 6.0 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| scicomp_molecular_mcp-0.1.2-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 12.0 kB
Release files / scicomp_molecular_mcp-0.1.2.tar.gz
| Download URL | scicomp_molecular_mcp-0.1.2.tar.gz |
|---|---|
| Size | 6.0 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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twine/6.1.0 CPython/3.13.7
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Transparency logRelease files / scicomp_molecular_mcp-0.1.2-py3-none-any.whl
| Download URL | scicomp_molecular_mcp-0.1.2-py3-none-any.whl |
|---|---|
| Size | 6.0 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
227a0ee42fa9ada202bd9e2c85a54b91bb0e304adccd5ae4f16c80ac0babc825
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| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/6.1.0 CPython/3.13.7
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Dec 31, 2025.
Transparency log