AgentTorch MCP Server
by AgentTorch
This server turns an LLM into a simulator using AgentTorch. It allows users to build, evaluate, and analyze simulations through a user-friendly interface.
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What is AgentTorch MCP Server?
The AgentTorch MCP Server is an interface that transforms AgentTorch into an MCP (Model-Controller-Player) server. It enables users to create, evaluate, and analyze simulations using an LLM-powered interface.
How to use AgentTorch MCP Server?
To use the server, first ensure you have the required Python packages and the ANTHROPIC_API_KEY environment variable set. Start the server using python server.py and access the interface at http://localhost:8000. You can then ask questions, run simulations, watch the real-time progress, and view the results and LLM-powered analysis.
Key features of AgentTorch MCP Server
Dark Mode UI
Claude-like Chat Interface
Real-time Visualization
LLM-powered Analysis
Sample Prompts
Use cases of AgentTorch MCP Server
Analyzing predator-prey dynamics
Exploring emergent behaviors in ecosystems
Simulating the impact of environmental changes
Analyzing population oscillations over time
Testing different simulation scenarios with LLM-powered insights
FAQ from AgentTorch MCP Server
What is AgentTorch?
What is AgentTorch?
AgentTorch is a framework used for building and running simulations.
What is the ANTHROPIC_API_KEY?
What is the ANTHROPIC_API_KEY?
This is the API key required to access the Claude LLM service used for analysis.
How do I install the required Python packages?
How do I install the required Python packages?
Run pip install -r requirements.txt in your terminal.
Where can I find the simulation data?
Where can I find the simulation data?
The simulation data is located in the services/data/18x25/ directory.
What is the purpose of the config.yaml file?
What is the purpose of the config.yaml file?
The config.yaml file contains the configuration settings for the AgentTorch simulation.