PyMemSim-MCP
Exposes membrane simulation capabilities through an MCP server, enabling gas hollow-fiber membrane simulations with dynamic thermodynamic model sources.
README
PyMemSim-MCP
PyMemSim-MCP exposes PyMemSim membrane simulation capabilities through an MCP server.
Overview ๐
PyMemSim-MCP is a next-generation framework that brings the Model Context Protocol into chemical engineering modeling and simulation, specifically for membrane-based separation systems.
Built on top of PyMemSim, this package introduces a model-source-driven architecture in which thermodynamic data, transport properties, and governing equations are defined externally in a structured, machine-readable format (e.g., YAML). These model sources are dynamically constructed using tools such as PyThermoLinkDB and PyThermoDB, and then supplied, alongside conventional inputs like temperature, pressure, and composition, to simulation workflows.
Unlike traditional tightly coupled simulation tools, PyMemSim-MCP decouples data, equations, and numerical solvers, enabling:
- โ Consistent and unit-safe thermodynamic definitions across simulations
- ๐ Flexible integration with multiple modeling packages and workflows
- โ๏ธ Solver-agnostic execution of mass and heat balance equations
- ๐ Transparent and interpretable simulation pipelines
A key innovation of PyMemSim-MCP is its compatibility with agentic workflows, where specialized agents can:
- ๐ง Extract and structure thermodynamic data from unstructured sources into validated model sources
- ๐ค Interact with MCP-enabled endpoints to perform simulations, sensitivity analysis, and optimization
This approach addresses critical gaps in current LLM-integrated engineering tools, where inconsistencies in data formats, units, and equations often lead to unreliable results. By enforcing a unified scientific contract, PyMemSim-MCP allows LLMs to control both conventional inputs and structured model sources before executing physics-based computations, significantly improving robustness and reproducibility.
PyMemSim-MCP is particularly suited for:
- ๐งช Membrane process modeling (e.g., hollow fiber modules, gas separation)
- ๐ค AI-assisted simulation workflows
- ๐ Rapid prototyping and validation of process models
- ๐ Educational and research applications in computational chemical engineering
Overall, PyMemSim-MCP represents a step toward trustworthy AI-driven simulation environments, where domain knowledge, data, and numerical methods are seamlessly integrated under a standardized and extensible framework.
Requirements ๐
- Python
>=3.11 pip(oruv)
Install the package ๐ฆ
pip install pymemsim-mcp
This installs the CLI entrypoint:
pymemsim-mcp
Start / Activate the MCP Server โถ๏ธ
The server entrypoint is:
- module:
python -m pymemsim_mcp.server - script:
pymemsim-mcp
Both support the same options.
Case A: STDIO transport (recommended for MCP desktop/agent clients) ๐งต
pymemsim-mcp --mode stdio
Equivalent:
python -m pymemsim_mcp.server --mode stdio
Case B: HTTP transport (for network-accessible clients) ๐
pymemsim-mcp --mode http --host 127.0.0.1 --port 8000 --path /mcp
Equivalent:
python -m pymemsim_mcp.server --mode http --host 127.0.0.1 --port 8000 --path /mcp
CLI Options โจ๏ธ
--mode:stdioorhttp(default:stdio)--host: HTTP bind host (default:127.0.0.1)--port: HTTP bind port (default:8000)--path: HTTP endpoint path (default:/mcp)
MCP Client Configuration Examples ๐
STDIO client config (generic)
{
"mcpServers": {
"pymemsim": {
"command": "pymemsim-mcp",
"args": ["--mode", "stdio"]
}
}
}
HTTP client config (generic)
{
"mcpServers": {
"pymemsim": {
"url": "http://127.0.0.1:8000/mcp"
}
}
}
Available Tool ๐งฉ
simulate_gas_hfm: build thermo model source from reference content and run gas hollow-fiber membrane simulation.
Development Quick Check โ
python -m py_compile pymemsim_mcp/server.py
python -m py_compile pymemsim_mcp/interface/gas_hfm.py
Troubleshooting ๐ฉบ
-
pymemsim-mcp: command not found- Run
pip install -e .in the active environment. - Confirm environment is activated.
- Run
-
Port already in use (HTTP mode)
- Change port, for example:
--port 8010.
- Change port, for example:
-
Import errors
- Reinstall dependencies:
pip install -e ..
- Reinstall dependencies:
โ FAQ
For any questions, contact me on LinkedIn.
๐ License
This project is licensed under the Apache License 2.0. See the LICENSE file for details.
๐จโ๐ป Authors
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.