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PhysiCell Multiscale Simulation Builder

  • 18 repo stars
  • Updated July 2, 2026
  • marcorusc/mcp-biomodelling-servers

PhysiCell is an MCP server that configures multiscale multicellular PhysiCell simulations through your agent.

About

PhysiCell Multiscale Simulation Developer is an MCP server that exposes configuration and setup workflows for PhysiCell multicellular simulations to AI coding agents. Developers and lab software authors use it when they are automating simulation prep—domains, cell types, parameters—inside Claude Code or Cursor instead of toggling between XML configs and chat. Install through uvx with mcp-biomodelling-servers and mcp-physicell-server. Pair it with other biomodelling MCP servers when a pipeline moves from pathway networks to spatial cell models. Complexity is advanced: PhysiCell builds, HPC habits, and biology context are on you. The MCP layer makes agent-driven iteration faster; it does not compile PhysiCell for you or guarantee biologically faithful results without expert review.

  • PhysiCell multiscale multicellular simulation configuration via MCP
  • Part of marcorusc mcp-biomodelling-servers suite on PyPI
  • Stdio transport with uvx runtimeHint
  • Positional server binary mcp-physicell-server
  • Version 1.0.0 with documented MCP server schema

PhysiCell Multiscale Simulation Builder by the numbers

  • Data as of Jul 28, 2026 (Skillselion catalog sync)
terminal
claude mcp add mcp-biomodelling-servers -- uvx mcp-biomodelling-servers

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repo stars18
Packagemcp-biomodelling-servers
TransportSTDIO
AuthNone
Last updatedJuly 2, 2026
Repositorymarcorusc/mcp-biomodelling-servers

What it does

Configure multiscale multicellular PhysiCell simulations from your agent when building computational biology or digital-twin prototypes.

Who is it for?

Best when you're embedding PhysiCell into agent-assisted research tools or custom simulation orchestration.

Skip if: Products with no cell-based modeling; teams seeking lightweight CSV or API mock servers only.

What you get

You get structured MCP steps to configure PhysiCell runs while coding, improving repeatability of simulation setups.

  • Agent-accessible PhysiCell configuration workflow
  • Stdio MCP registration for multiscale simulation builds

By the numbers

  • Server version 1.0.0
  • Transport: stdio
  • Entry: mcp-physicell-server
README.md

MCP Bio‑Modelling Servers

PyPI MCP Registry

This repository centralizes Model Context Protocol (MCP) servers that wrap Python‑based mechanistic / systems biology modelling tools. Each subfolder contains a server.py entrypoint plus a README describing the specific tool interface.

Current servers (see their own READMEs & upstream docs):

Tool Folder Upstream Documentation MCP Registry
MaBoSS MaBoSS/ https://github.com/colomoto/pyMaBoSS io.github.marcorusc/MaBoSS
NeKo NeKo/ https://github.com/sysbio-curie/Neko io.github.marcorusc/NeKo
PhysiCell (settings wrapper) PhysiCell/ https://github.com/marcorusc/PhysiCell_Settings io.github.marcorusc/PhysiCell

All servers are Python processes speaking MCP over stdio.


Installation

Option A — pip (recommended)

pip install mcp-biomodelling-servers

Then run any server directly:

mcp-neko-server
mcp-maboss-server
mcp-physicell-server

Option B — uvx (no install needed)

uvx --from mcp-biomodelling-servers mcp-neko-server
uvx --from mcp-biomodelling-servers mcp-maboss-server
uvx --from mcp-biomodelling-servers mcp-physicell-server

Option C — from source (Conda, full control)

Clone this repo and set up a Conda environment with all dependencies (see Environment Assumption below).


MCP Background

The Model Context Protocol standardizes how external tools expose tools and resources to AI assistants / IDEs. Spec & introduction: https://modelcontextprotocol.io/docs/getting-started/intro

Each server.py advertises modelling actions (e.g. run simulations, manage sessions) to any MCP‑aware client (e.g. VS Code with GitHub Copilot Chat MCP support).


Repository Layout

MaBoSS/    # MaBoSS MCP server (Boolean / stochastic models)
NeKo/      # NeKo MCP server
PhysiCell/ # PhysiCell settings / sessions MCP server
README.md

Consult the README within each tool folder for: purpose, required Python packages, and any model/data file expectations. Installation instructions for the modelling tools themselves live there (or in the upstream project links above) — they are intentionally not duplicated here.


Environment Assumption

All tools are Python‑based. Create (and manage) a single Conda environment that contains the dependencies for MaBoSS, NeKo, and PhysiCell. The exact creation commands are up to you (not prescribed here). Once created, note the absolute path to its Python interpreter (e.g. /home/you/miniforge3/envs/mcp_modelling/bin/python).


Configure in VS Code (GitHub Copilot Chat / MCP)

  1. Open VS Code and ensure the Copilot Chat (or other MCP-capable) extension is installed.
  2. Press Ctrl + Shift + P → "MCP: Open Configuration" (or edit ~/.config/Code/User/mcp.json directly).
  3. Add entries for each server.

Simple setup (uvx / pip install)

If you installed via pip or want to use uvx, no paths are needed:

{
  "servers": {
    "neko": {
      "type": "stdio",
      "command": "uvx",
      "args": ["--from", "mcp-biomodelling-servers", "mcp-neko-server"]
    },
    "maboss": {
      "type": "stdio",
      "command": "uvx",
      "args": ["--from", "mcp-biomodelling-servers", "mcp-maboss-server"]
    },
    "physicell": {
      "type": "stdio",
      "command": "uvx",
      "args": ["--from", "mcp-biomodelling-servers", "mcp-physicell-server"]
    }
  }
}

Advanced setup (Conda environment, from source)

Use this if you need a custom Conda environment (e.g. for native MaBoSS binaries or local development):

{
  "servers": {
    "maboss": {
      "type": "stdio",
      "command": "/home/you/miniforge3/envs/mcp_modelling/bin/python",
      "args": [
        "/absolute/path/to/mcp-biomodelling-servers/MaBoSS/server.py"
      ],
      "env": {
        "PATH": "/home/you/miniforge3/envs/mcp_modelling/bin:${Path}",
        "CONDA_PREFIX": "/home/you/miniforge3/envs/mcp_modelling"
      }
    },
    "neko": {
      "type": "stdio",
      "command": "/home/you/miniforge3/envs/mcp_modelling/bin/python",
      "args": [
        "/absolute/path/to/mcp-biomodelling-servers/NeKo/server.py"
      ]
    },
    "physicell": {
      "type": "stdio",
      "command": "/home/you/miniforge3/envs/mcp_modelling/bin/python",
      "args": [
        "/absolute/path/to/mcp-biomodelling-servers/PhysiCell/server.py"
      ]
    }
  }
}

Replace /home/you/... and /absolute/path/to/... with your actual directories. Keep all three servers referencing the same Conda interpreter to share installed libraries.

After saving, reload / restart VS Code so the MCP client reconnects.

Activation / usage guidance in VS Code: https://code.visualstudio.com/docs/copilot/chat/mcp-servers

You should then see the servers' tools listed in the Copilot Chat "/tools" (or similar) UI. Invoke them by name with required parameters.

Adding Another Server

  1. Create a new folder with server.py and a README describing the underlying modelling tool and dependencies.
  2. Follow existing server structure for registering MCP tools.
  3. Update your mcp.json with a new block (use the same Conda Python path).
  4. Document any additional env vars in that folder README.

License

Project is MIT (see existing LICENSE file). Underlying tools retain their own licenses — consult upstream repositories.


Quick Reference

Action What to Do
Get tool install steps Open the tool’s subfolder README or upstream link
Ensure deps present Install into your chosen Conda env (user‑defined)
Configure MCP Edit ~/.config/Code/User/mcp.json as above
Reload servers Reload VS Code window
Learn MCP Spec: modelcontextprotocol.io; VS Code guide link above

Happy modelling!

Recommended MCP Servers

How it compares

Multicellular simulation config MCP, not NeKo pathway graphs or spreadsheet DuckDB tooling.

FAQ

Who is PhysiCell MCP for?

Developers and computational biology developers who use agents daily and need PhysiCell configuration callable as MCP tools.

When should I use PhysiCell MCP?

During build when you integrate PhysiCell into automated or agent-guided simulation workflows before production hardening.

How do I add PhysiCell to my agent?

Configure stdio MCP with uvx, --from mcp-biomodelling-servers, and mcp-physicell-server per io.github.marcorusc/PhysiCell server.json.

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