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  3. MaBoSS Boolean Network Simulator
MaBoSS Boolean Network Simulator logo
Health: ActiveRecent health check succeeded.Last checked 9/7/2026, 9:27:40 PM

MaBoSS Boolean Network Simulator

User RatingsBe the first to rate and review this MCP server! Enrichment pendingWe haven’t run our AI enrichment pass on this listing yet, so the overview, use cases, and FAQ below may be sparse or missing. We work through the catalog over time β€” check back soon.
View Repository18 GitHub StarsTotal stargazers on GitHub for the source repository (18 stars).Visit Website

MCP server for Boolean network simulation and attractor analysis using MaBoSS

Quick Install

Automated & IDE Setup

Copy the AI prompt to install this server into Claude Code, Cursor, or another agent β€” or use 1-click editor setup below.

Add to CursorAdd to VS Code
Not yet automatically verified

We haven't yet run this listing's install command through our automated sandbox check. This isn't a red flag β€” we're steadily working through the catalog.

Manual Client & Custom JSON ConfigExpand JSON β–Ύ

Client Config & Setup

Choose your client or environment
Target File:~/Library/Application Support/Claude/claude_desktop_config.json
claude_desktop_config.json
{
  "mcpServers": {
    "maboss-boolean-network-simulator": {
      "command": "uvx",
      "args": [
        "--from"
      ]
    }
  }
}

πŸ’‘ Paste the JSON block into your client's configuration file under mcpServers, then restart the application.

Install Directory Badge Claim listing AlternativesπŸ’» More in Developer Tools

Documentation Overview

MCP Bio-Modelling Servers

PyPI MCP Registry

This package provides three stateful Model Context Protocol servers for mechanistic and systems-biology modelling:

ServerModelling roleUpstream projectMCP Registry name
MaBoSSConfigure, simulate, and analyze stochastic Boolean modelspyMaBoSSio.github.marcorusc/MaBoSS
NeKoBuild and analyze signalling networks from interaction databasesNeKoio.github.marcorusc/NeKo
PhysiCellBuild, inspect, and export PhysiCell and PhysiBoSS configuration filesPhysiCell-settingsio.github.marcorusc/PhysiCell

All three servers use MCP over stdio and are distributed together as mcp-biomodelling-servers.

Publication

For more details, please check the related article:

"Intelligent tool orchestration for rapid mechanistic model prototyping: MCP servers as AI-biology interfaces"
Marco Ruscone, Miguel Vazquez & Alfonso Valencia, npj Systems Biology and Applications (2026)
https://doi.org/10.1038/s41540-026-00767-3

Requirements

  • Python 3.10–3.14.
  • MCP Python SDK 2.x, installed automatically with this package.
  • The modelling-package dependencies declared in pyproject.toml, installed automatically by pip or uvx.
  • The Graphviz system runtime for NeKo history diagrams. The Python graphviz package is not a replacement for the external dot renderer.

Check whether Graphviz is available with:

bash
dot -V

If this command is missing, install Graphviz using your operating system or environment package manager. See the Graphviz installation guide for platform-specific instructions.

Installation

Install with pip

bash
python -m pip install mcp-biomodelling-servers

The installation provides three console entry points:

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

Run in an isolated environment with uvx

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

Conda is optional. It remains useful when you want one explicitly managed environment for local development or additional native scientific software, but it is not required for the packaged entry points.

Configure an MCP client

The following example uses uvx and works with clients that accept the common mcp.json stdio configuration:

JSON Config
{
  "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"
      ]
    }
  }
}

If the package is already installed in the client environment, each entry can instead use its console script directly:

JSON Config
{
  "servers": {
    "neko": {
      "type": "stdio",
      "command": "mcp-neko-server"
    },
    "maboss": {
      "type": "stdio",
      "command": "mcp-maboss-server"
    },
    "physicell": {
      "type": "stdio",
      "command": "mcp-physicell-server"
    }
  }
}

Refer to your MCP client's documentation for its configuration-file location and reload procedure. For Visual Studio Code, see Use MCP servers in VS Code.

Sessions, artifacts, and errors

Each server can maintain multiple isolated modelling sessions. Tools that create or load a model return a session identifier; pass that identifier to subsequent operations when more than one session is active.

Generated models, configuration files, plots, and other outputs are kept in session-scoped artifact directories. Artifact-listing tools return the paths needed to inspect or hand files to another modelling server.

Under MCP SDK 2.x, failures to execute a tool are returned as tool errors so the client and model can distinguish them from successful scientific results. Validation tools may still return a successful result describing an invalid model or configuration when validity itself is the requested result.

Run from source

Clone the repository and install it with its development dependencies:

bash
git clone https://github.com/marcorusc/mcp-biomodelling-servers.git
cd mcp-biomodelling-servers
python -m pip install ".[dev]"

You can then run the same console entry points or invoke a server module directly with the selected Python interpreter:

bash
python MaBoSS/server.py
python NeKo/server.py
python PhysiCell/server.py

Repository layout

text
MaBoSS/                     MaBoSS server, manual, and Registry manifest
NeKo/                       NeKo server, manual, and Registry manifest
PhysiCell/                  PhysiCell server, manual, and Registry manifest
mcp_biomodelling_servers/   Installed package namespace and entry points
tests/                      Protocol, runtime, concurrency, and package tests

The server-specific READMEs describe the modelling workflows and exposed tool families in more detail.

MCP SDK and protocol compatibility

The package uses the stable MCP Python SDK 2.x API. The SDK negotiates the appropriate MCP protocol revision with the connected client; the protocol revision is independent of the MCP Registry schema used by each server.json.

License

The package metadata declares the project under the MIT license. The wrapped modelling packages retain their own licenses; consult their upstream projects for details.

Read the full README β†’View source on GitHub β†’

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Reviews

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Frequently Asked Questions about MaBoSS Boolean Network Simulator

Add the following block to your claude_desktop_config.json under mcpServers: "mcpServers": { "maboss-boolean-network-simulator": { "command": "npx", "args": ["-y", "MaBoSS Boolean Network Simulator"] } }

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Technical Specs & Signals

CategoryπŸ’»Developer Tools
More technical detailsExpand β–Ύ
TransportSTDIO
RuntimePython
Last updatedSep 7, 2026
Views0
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Installs0
Installs & Copy ActionsTotal times users copied install commands or configuration snippets for this server.
GitHub stars18
GitHub Star CountTotal stargazers on GitHub representing community popularity (18 stars).
37Quality signal: Fair Β· 37/100How this signal is calculated β–Ύ
Server availabilityNot measured

Not scored for repo-hosted servers β€” we can't reach the running server, only its GitHub page. Hosted MCP endpoints are health-checked live.

Verified ownership10/20
Documentation & tools15/30
Adoption & activity3/15
Community engagement0/10

A guidance signal from public completeness & health data β€” not a user rating. New listings start lower and rise as they add docs, get verified, and grow adoption. Signals we can't observe for a listing are skipped, not counted against it.

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