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Create, run, and analyze NetLogo agent-based models conversationally.
Copy the install command and let the AI configure it · recommended for beginners
Please install the "NetLogo MCP" MCP server from askskill: Run: claude mcp add 'io-github-razee4315-netlogo-mcp' -- npx -y netlogo-mcp
Create a basic SIR epidemic model in NetLogo with susceptible, infected, and recovered agents. Make infection and recovery rates adjustable, and explain what each parameter does.
A runnable NetLogo model, parameter explanations, and guidance for starting and observing the spread.
Using an existing NetLogo model, run batch tests on how population density and movement speed affect outcomes, and provide a comparison approach for key metrics.
An experiment plan, suggested parameter combinations, and an analysis framework for trends and key metrics.
I have already run a NetLogo traffic congestion model. Help me interpret the results, identify possible causes of congestion, and suggest variables to test next.
An interpretation of results, analysis of possible mechanisms, and recommendations for follow-up experiments and model improvements.
Build, debug, and manage software tasks with natural language across LLMs.
Build, validate, and monitor data pipelines from natural language requests.
Connect AI agents to control local JupyterLab for coding and analysis.
Give AI agents structured access to networking standards, device databases, and security data.
Generate runnable AnyLogic simulation models from natural-language prompts.
Simulate dynamic actions for any query with persistent state across sessions.