Skip to main content

The first MCP server for NetLogo — let AI assistants create, run, and analyze agent-based models through natural conversation

Project description

NetLogo MCP

PyPI CI Python 3.10+ Ruff mypy MIT License

The first MCP (Model Context Protocol) server for NetLogo — enabling AI assistants to create, run, and analyze agent-based models through natural conversation.

Works with: Claude Code, Claude Desktop, Cursor, Windsurf, VS Code (Copilot), Cline, Continue, Roo Code, Zed, OpenCode, Codex — any tool that supports MCP.

Why NetLogo MCP?

As an AI student taking an Agent-Based Modeling course, I searched for an MCP server to control NetLogo — nothing existed. So I built one.

Instead of manually writing NetLogo code, clicking buttons, and tweaking sliders, you tell your AI assistant what you want in plain English:

"Create a predator-prey model with 100 sheep and 20 wolves. Run it for 500 ticks and show me the population dynamics."

The AI writes the code, runs the simulation, and shows you the results — all through conversation.

You (in any MCP client) → AI Assistant → MCP Protocol → NetLogo MCP Server → NetLogo (GUI or headless JVM)

By default a real NetLogo window opens (on first use) so you can watch your simulations run live. Headless mode is available for CI or servers.

Features

  • Create models from code — with real interface widgets: sliders, switches, buttons, monitors
  • Run simulations and collect tick-by-tick data as markdown tables
  • Run BehaviorSpace experiments — parallel parameter sweeps via the headless launcher
  • Export the view as PNG — visible inline in chat
  • Inspect everything — world state, agent samples, patch grids for heatmaps
  • CoMSES Net integration — search and safely run models from the largest peer-reviewed ABM library
  • Built-in references — NetLogo primitives, programming guide, and 6→7 transition guide as MCP resources
  • Lazy startup — the NetLogo window only opens when you actually use a tool, not when your AI client connects

See docs/TOOLS.md for the full reference of all 25 tools, widget schema, and prompts.

Prerequisites

Requirement Install via terminal? How
Python 3.10+ Yes Windows: winget install Python.Python.3.12 · macOS: brew install python@3.12 · Linux: sudo apt install python3.12
Java JDK 11+ Yes Windows: winget install EclipseAdoptium.Temurin.21.JDK · macOS: brew install --cask temurin · Linux: sudo apt install openjdk-21-jdk
NetLogo 7.0+ No — manual Download from ccl.northwestern.edu/netlogo

Only NetLogo requires manual download. Everything else can be installed via terminal, and the Zero-Config Setup prompt below handles those automatically.

Zero-Config Setup (Recommended)

If you're using an AI coding tool, copy the prompt below into your chat. The AI will detect your OS, find your NetLogo and Java installations, clone the repo, install dependencies, configure your MCP client, and tell you how to use it.

Click to copy the setup prompt
Please set up the NetLogo MCP server for me end-to-end. Follow these steps carefully:

1. **Detect my environment**
   - Identify my OS (Windows / macOS / Linux).
   - Check Python version (need 3.10+). If missing, tell me to install it first and stop.
   - Check for Java JDK 11+ (not JRE). Look in common locations (JAVA_HOME env var, standard install dirs). If missing, tell me to install Adoptium Temurin JDK 11+ and stop.
   - Check for NetLogo 7.0+. Look in common locations:
     - Windows: `C:/Program Files/NetLogo*`
     - macOS: `/Applications/NetLogo*`
     - Linux: `/opt/netlogo*`, `~/netlogo*`
     If NetLogo isn't installed, tell me to download it from https://ccl.northwestern.edu/netlogo/download.shtml and stop.

2. **Install**
   - Run: `pip install netlogo-mcp`
   - Verify the `netlogo-mcp` command is now available on my PATH.

3. **Identify my MCP client**
   - Figure out which AI tool I'm using (Claude Code, Cursor, Windsurf, Cline, Continue, Roo Code, Zed, OpenCode, VS Code Copilot, Codex, or Claude Desktop).
   - If you're not sure, ask me.

4. **Configure the MCP client**
   - Locate (or create) the correct config file for my client (see
     https://github.com/Razee4315/NetLogo-MCP/blob/main/docs/CLIENTS.md
     for exact paths and schemas per client).
   - Add a `netlogo` server entry with:
     - `command`: `netlogo-mcp`
     - `env.NETLOGO_HOME`: the NetLogo path you detected
     - `env.JAVA_HOME`: the JDK path you detected
   - Use the exact JSON schema for my specific client (e.g. `"type": "stdio"` for Cursor, `"servers"` key for VS Code).
   - Preserve any existing config entries — merge, don't overwrite.
   - IMPORTANT: configure it for THIS project only (project-scope config file), not globally, unless I say otherwise — a global entry loads the server in every session.

5. **Tell me what to do next**
   - Tell me to fully restart my AI tool for the new MCP server to load.
   - Tell me the NetLogo window opens on the FIRST model tool call, and that call takes 30–60 seconds while the Java Virtual Machine starts. Tell me NOT to click stop during this wait.
   - Give me this exact test prompt to try after restart:

     > "Create a simple predator-prey model with wolves and sheep on a green landscape. Run setup, then run 100 ticks while tracking wolf and sheep counts. Export the view before and after so I can see how the world evolved."

   - Tell me where models and exports are saved (by default, the current working directory's `models/` and `exports/` folders) and that I can browse them with the `list_models` tool.

Do not skip any verification step. If something fails, stop and tell me exactly what failed and how to fix it.

Manual Installation

pip install netlogo-mcp

Then add the server to your MCP client. For Claude Code, add to your project's .mcp.json:

{
  "mcpServers": {
    "netlogo": {
      "command": "netlogo-mcp",
      "args": [],
      "env": {
        "NETLOGO_HOME": "C:/Program Files/NetLogo 7.0.3",
        "JAVA_HOME": "C:/Program Files/Eclipse Adoptium/jdk-25.0.2.10-hotspot"
      }
    }
  }
}

Restart Claude Code and verify with /mcp.

Tip: prefer project-scope config (.mcp.json in one project) over global config — a global entry loads the server in every session of every project.

Using Cursor, Windsurf, VS Code, Cline, Continue, Roo Code, Zed, OpenCode, Codex, or Claude Desktop? See docs/CLIENTS.md for exact config for all 11 clients. All configuration options (GUI/headless mode, directories, limits) are in docs/CONFIGURATION.md.

Developing or contributing? Clone the repo and install editable instead:

git clone https://github.com/Razee4315/NetLogo-MCP.git
cd NetLogo-MCP
pip install -e ".[dev]"

Quick Start

Once connected, try these prompts in any MCP client:

> Create a simple NetLogo model with 50 turtles doing a random walk.
  Run setup, simulate 100 ticks, and export the view.

> Open the Wolf Sheep Predation model and run a parameter sweep
  on initial-number-wolves from 10 to 100.

> Build a disease spread model with sliders for population size and
  infection chance.

The first model tool call takes 30-60 seconds while the JVM starts — the NetLogo window appears when it's ready. Don't click stop. Every call after that is instant.

Troubleshooting

Problem Solution
NETLOGO_HOME is not set Set the environment variable to your NetLogo install directory
JAVA_HOME is not set Set it to your JDK directory (not JRE)
JVM crashes on startup Make sure JAVA_HOME points to JDK 11+, not an older version
No model is loaded Call open_model or create_model before using other tools
First model call hangs for 30-60s Normal — JVM is warming up. Don't click stop.
NetLogo window opens when my AI client starts You have NETLOGO_EAGER_START=true set, or an old version — by default the window only opens on first tool use
Server won't connect Run netlogo-mcp manually in terminal to see error output

Documentation

Listed on

MCP Badge

Citing

If you use NetLogo MCP in research or teaching, please cite it — click "Cite this repository" in the GitHub sidebar, or see CITATION.cff.

Author

Saqlain Abbas Email: saqlainrazee@gmail.com GitHub: @Razee4315 LinkedIn: @saqlainrazee

License

This project is licensed under the MIT License — free to use, modify, and distribute for any purpose.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

netlogo_mcp-1.0.2.tar.gz (137.4 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

netlogo_mcp-1.0.2-py3-none-any.whl (83.8 kB view details)

Uploaded Python 3

File details

Details for the file netlogo_mcp-1.0.2.tar.gz.

File metadata

  • Download URL: netlogo_mcp-1.0.2.tar.gz
  • Upload date:
  • Size: 137.4 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.12

File hashes

Hashes for netlogo_mcp-1.0.2.tar.gz
Algorithm Hash digest
SHA256 d97d8934384f4dafbe2ba7b790c0c54d4db263aab0773ddb8ac057542f9c0050
MD5 6e8c6afa5fbe8ad11cce192da1d2f310
BLAKE2b-256 6fb15fb6672749bf774f479a6a804eb32cf0a0b1bc96fefa08784e3deca0d511

See more details on using hashes here.

Provenance

The following attestation bundles were made for netlogo_mcp-1.0.2.tar.gz:

Publisher: release.yml on Razee4315/NetLogo-MCP

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file netlogo_mcp-1.0.2-py3-none-any.whl.

File metadata

  • Download URL: netlogo_mcp-1.0.2-py3-none-any.whl
  • Upload date:
  • Size: 83.8 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.12

File hashes

Hashes for netlogo_mcp-1.0.2-py3-none-any.whl
Algorithm Hash digest
SHA256 917301f5179265fc56710ca39c5bfc27192263e080b84a0d3c4ec8fba7226912
MD5 f45efbe532686f5a5a200a7e1f42038a
BLAKE2b-256 db7d2f9b750e44baae965ae28c07e19443c97c4b087cd25e4765e671f2cfaa05

See more details on using hashes here.

Provenance

The following attestation bundles were made for netlogo_mcp-1.0.2-py3-none-any.whl:

Publisher: release.yml on Razee4315/NetLogo-MCP

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page