Stella MCP Server

A Model Context Protocol (MCP) server for creating and manipulating Stella system dynamics models. This enables AI assistants like Claude to programmatically build, read, validate, and save .stmx files in the XMILE format.

What is this for?

Stella is a system dynamics modeling tool used for simulating complex systems in fields like ecology, biogeochemistry, economics, and engineering. This MCP server allows AI assistants to:

• Create models from scratch - Build stock-and-flow diagrams programmatically
• Read existing models - Parse and understand .stmx files
• Validate models - Check for errors like undefined variables or missing connections
• Modify models - Add stocks, flows, auxiliaries, and connectors
• Save models - Export valid XMILE files that open in Stella Professional

This is particularly useful for:

• Teaching system dynamics modeling
• Rapid prototyping of models through natural language
• Batch creation or modification of models
• Documenting and explaining existing models

Installation

From PyPI

pip install stella-mcp

From source

git clone https://github.com/bradleylab/stella-mcp.git
cd stella-mcp
pip install -e .

Requirements

• Python 3.10+
• mcp>=1.0.0

Configuration

Claude Desktop

Add to your claude_desktop_config.json:

{
  "mcpServers": {
    "stella": {
      "command": "stella-mcp"
    }
  }
}

Claude Code

Add to your .claude/settings.json:

{
  "mcpServers": {
    "stella": {
      "command": "stella-mcp"
    }
  }
}

Development mode

If running from source:

{
  "mcpServers": {
    "stella": {
      "command": "python",
      "args": ["-m", "stella_mcp.server"],
      "cwd": "/path/to/stella-mcp"
    }
  }
}

Available Tools

Model Creation & I/O

Model Building

Model Inspection

Example Usage

Creating a simple population model

User: Create a simple exponential growth model with a population starting at 100
      and a growth rate of 0.1 per year

Claude: [Uses create_model, add_stock, add_aux, add_flow, add_connector, save_model]
        Creates population_growth.stmx with:
        - Stock: Population (initial=100)
        - Aux: growth_rate (0.1)
        - Flow: growth (Population * growth_rate) into Population

Reading and analyzing an existing model

User: Read the carbon cycle model and explain what it does

Claude: [Uses read_model, list_variables]
        This model has 3 stocks (Atmosphere, Land Biota, Soil) and 6 flows
        representing carbon exchange through photosynthesis, respiration...

Building a biogeochemical model

User: Create a two-box ocean model with surface and deep nutrients

Claude: [Uses create_model, add_stock (x4), add_aux (x8), add_flow (x6), save_model]
        Creates a model with nutrient cycling between surface and deep ocean
        including upwelling, downwelling, biological uptake, and remineralization

Validation

The validate_model tool checks for:

• Undefined variables - References to variables that don't exist
• Mass balance issues - Stocks without flows, flows referencing non-existent stocks
• Missing connections - Equations using variables without connectors (warning)
• Orphan flows - Flows not connected to any stock
• Circular dependencies - Infinite loops in auxiliary calculations

XMILE Compatibility

• Output files use the XMILE standard
• Compatible with Stella Professional 1.9+ and Stella Architect
• Auto-layout positions elements reasonably; adjust manually in Stella if needed
• Variable names with spaces are converted to underscores internally

Project Structure

stella-mcp/
├── README.md
├── LICENSE
├── pyproject.toml
└── stella_mcp/
    ├── __init__.py
    ├── server.py      # MCP server implementation
    ├── xmile.py       # XMILE XML generation and parsing
    └── validator.py   # Model validation logic

Contributing

Contributions are welcome! Please feel free to submit issues or pull requests.

License

MIT License - see LICENSE for details.

Acknowledgments

• Model Context Protocol by Anthropic
• ISEE Systems for Stella and the XMILE format