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Stella MCP logo
Health: ActiveRecent health check succeeded.Last checked 9/9/2026, 1:32:20 PM

Stella MCP

User RatingsBe the first to rate and review this MCP server!
View Repository3 GitHub StarsTotal stargazers on GitHub for the source repository (3 stars).Visit Website
system-dynamicsmodelingsimulationxmilestella

Create, read, validate, modify, and save Stella system dynamics models (.stmx XMILE files) programmatically.

Quick Install

Automated & IDE Setup

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

Add to CursorAdd to VS Code
Automated check passed— started and listed 42 tools correctly (1mo ago).
Manual Client & Custom JSON ConfigExpand JSON ā–¾

Client Config & Setup

Choose your client or environment
Target File:~/Library/Application Support/Claude/claude_desktop_config.json
claude_desktop_config.json
{
  "mcpServers": {
    "bradleylab-stella-mcp": {
      "command": "uvx",
      "args": [
        "stella-mcp"
      ]
    }
  }
}

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

Install Tool Schemas (42) Directory Badge Claim listing Alternatives🧮 More in Data Science Tools

Overview

This MCP server enables AI agents to programmatically create, read, validate, modify, and save Stella system dynamics models in the .stmx XMILE format. It supports building stock-and-flow diagrams, managing variables and connectors, and exporting models compatible with Stella Professional. Use it for automating model creation, batch editing, teaching system dynamics, or documenting existing models.

Use cases

•Create new system dynamics models programmatically
•Read and parse existing .stmx Stella model files
•Validate models for errors and missing connections
•Modify models by adding or updating stocks, flows, auxiliaries, and connectors
•Save models as valid XMILE files for Stella Professional

Key features

•Build and populate models atomically with batch tools
•Add, update, rename, and delete stocks, flows, auxiliaries, and modules
•Manage connectors including automatic syncing from equations
•Load and save models with configurable simulation time settings
•Support templates for reusable model components
•Simulate models for behavior sanity checks (with sim extra)

Capabilities & Tool Schemas (42) ~10.0k tokensApproximate context cost of this server’s tool schemas (~4 chars/token), before any tool is called. Actual usage depends on your client and model.Verified live Verified liveCaptured by calling this server’s live tools/list endpoint.

Inspect callable tools, capabilities, and parameters exposed to AI agents by Stella MCP.

create_model

Create a new Stella model with specified time settings

build_model

Create and populate a model in one call: sim specs, stocks, auxiliaries, flows, connectors, and modules. All-or-nothing — on any item error nothing is registered and the error names the failing item (stage + index). Connector sync and validation run by default, so the response doubles as an inspection.

add_variables

Add multiple stocks, auxiliaries, flows, connectors, and/or modules to an existing model in one call. All-or-nothing — on any item error the model is left unchanged and the error names the failing item (stage + index).

set_sim_specs

Update simulation time settings on an existing model

add_stock

Add a stock (reservoir) to the current model

update_stock

Update stock fields while preserving relationships

Documentation Overview

Stella MCP Server

A vendor-neutral Model Context Protocol (MCP) server for creating and manipulating Stella system dynamics models. Any compliant MCP client can build, read, validate, and save .stmx files in the XMILE format; optional host features still vary.

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

Terminal
pip install stella-mcp

From source

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

Requirements

  • Python 3.10+
  • mcp>=2.0.0,<3

Configuration

Via uvx (no install required)

If you have uv installed, the lowest-friction configuration runs the published package directly:

config.json
{
  "mcpServers": {
    "stella": {
      "command": "uvx",
      "args": ["stella-mcp"]
    }
  }
}

Claude Desktop

Add to your claude_desktop_config.json:

config.json
{
  "mcpServers": {
    "stella": {
      "command": "stella-mcp"
    }
  }
}

Claude Code

Add to your .claude/settings.json:

config.json
{
  "mcpServers": {
    "stella": {
      "command": "stella-mcp"
    }
  }
}

Development mode

If running from source:

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

Recommended Agent Workflow

For a new model:

  1. On MCP 2026-07-28, call create_workspace and carry the returned workspace_id through stateful calls. Legacy stdio clients may omit it.
  2. build_model with a stable model_id and the full set of stocks, auxiliaries, and flows in one call (connector sync and validation run by default, so the response doubles as an inspection).
  3. Fix validation errors with update_*, rename_variable, or delete_variable.
  4. Extend incrementally with add_variables (batch) or the single-add tools.
  5. simulate to sanity-check behavior (requires the sim extra).
  6. Save with save_model.

For imported models:

  1. read_model with compat_mode="permissive" to inspect warnings.
  2. Run inspect_model to understand model structure.
  3. Use compat_mode="strict" before final save when round-trip fidelity matters.

Available Tools

Model Creation & I/O

ToolDescription
create_modelCreate a new model with name and time settings (start, stop, dt, method)
set_sim_specsUpdate simulation time settings on an existing model
read_modelLoad an existing .stmx file
save_modelSave model to a .stmx file
delete_modelRemove a model from the workspace (saved files untouched)

Templates

ToolDescription
list_templatesList built-in and user-defined templates (supports source/query/tag filters)
get_template_infoGet detailed metadata for one template
load_templateLoad a template as a model in the current workspace
save_as_templateSave the current model as a reusable user template (optional description/tags)

Model Building

ToolDescription
build_modelCreate and populate a model in one call (atomic batch)
add_variablesAdd multiple variables/connectors/modules to an existing model (atomic batch)
add_stockAdd a stock (reservoir) with initial value and units
add_flowAdd a flow between stocks with an equation
add_auxAdd an auxiliary variable (parameter or calculation)
update_stockUpdate stock fields while preserving relationships
update_flowUpdate flow fields while preserving stock links
update_auxUpdate auxiliary variable fields
add_connectorAdd a dependency connector between variables
sync_connectors_from_equationsAdd missing dependency connectors inferred from equations
set_connector_routingSet connector angle and explicit waypoint routing metadata
rename_variableRename a stock/flow/aux and update references in equations/connectors/modules
delete_variableDelete a stock/flow/aux with consistency checks and cleanup
create_moduleCreate a logical module/group of variables
add_to_moduleAdd variables to an existing module/group
remove_from_moduleRemove variables from a module/group
rename_moduleRename a module/group
delete_moduleDelete a module/group
set_module_viewSet explicit module box position/size on the diagram
set_module_styleSet module box style (border/background/font/label side) on the diagram
auto_place_module_boxesAuto-place module boxes around their members

Notes:

  • MCP 2026-07-28 clients call create_workspace once and include its returned workspace_id in stateful calls. Modern tool discovery marks that field as required on stateful tools. The ID routes application state; it is not an authorization credential.
  • Supported legacy stdio clients may omit workspace_id and use one process-local compatibility workspace; legacy discovery keeps the field optional.
  • Tools accept optional model_id so one workspace can manage multiple models safely.
  • create_model and read_model set the workspace's current model_id and return it.
  • add_flow and add_aux support optional graphical_function payloads (ypts plus exactly one of xscale or xpts).
  • add_stock/add_flow/add_aux reject duplicate variable names across variable types; add_connector requires both variables to exist.
  • set_connector_routing can target a connector by connector_uid or by from_var + to_var.
  • save_model and get_model_xml accept auto_layout (default true) and resolve_layout_violations (default false).
  • save_model, get_model_xml, and render_diagram return the latest layout viewport, metrics, and warnings in structured content. Their text result names any non-clean layout warning codes.
  • read_model, save_model, and get_model_xml accept compat_mode:
    • permissive (default): continue with warnings
    • strict: fail on compatibility issues
  • set_module_style updates module view styling and persists those attributes in XMILE view <group .../> elements.
  • save_as_template writes user templates to ~/.stella-mcp/templates by default (override via STELLA_MCP_TEMPLATE_DIR) and stores metadata in a .meta.json sidecar.
  • Tool failures return structured MCP errors with error.code, error.category, and error.message.
  • Every successful tool result retains readable text and supplies schema-validated structuredContent described by its JSON Schema 2020-12 outputSchema.

Workspace Lifecycle

ToolDescription
create_workspaceCreate an isolated workspace, optionally with a caller-selected lifetime
revoke_workspaceRevoke a workspace and discard its in-memory models

Model Inspection

ToolDescription
list_modelsList available workspace model IDs and indicate the current model
inspect_modelReturn a structured model summary for agent inspection
list_modulesList modules/groups in the current model
list_connectorsList connector IDs, endpoints, angles, and routing metadata
list_variablesList all stocks, flows, and auxiliaries
validate_modelCheck for errors (undefined variables, missing connections, etc.)
get_model_xmlPreview the XMILE XML output
render_diagramRender the model as an SVG stock-and-flow diagram
simulateRun the model via PySD and return time series + summaries (sim extra)
compare_scenariosRun named what-if override sets against a baseline and report deltas (sim extra)
sensitivity_analysisSweep parameters one-at-a-time and rank their effect on an output metric (sim extra)
calibrateFit constant parameters to an observed time-series (inverse of simulate) (sim extra)

Batch Building

build_model creates and populates a model in one call. Items apply in the order stocks → auxs → flows → connectors → modules; the whole batch is all-or-nothing, and on failure the error names the failing item (error.stage + error.index). The same item arrays work on an existing model via add_variables.

Read the full README →View source on GitHub →

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Adoption & maintenance

Factual signals from GitHub, npm, and our automated checks — not a rating.

GitHub stars
3
Stargazers on the source repository.
Last commit
1mo ago
Most recent push to the default branch.
Availability
100%
Our rolling endpoint + install checks that succeeded.
Install check
Passed
Our sandbox started it and listed its tools.
Tools exposed
42
Callable tools this server registers over MCP.
Directory activity
2 views
Config copies, upvotes, and views on AllMCPs.

Reviews

No reviews yet — be the first to share how this listing worked for you.

Frequently Asked Questions about Stella MCP

It uses the .stmx file format, which is Stella's XMILE-based system dynamics model format.

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Technical Specs & Signals

Category🧮Data Science Tools
PricingFree
More technical detailsExpand ā–¾
TransportSTDIO
RuntimePython
AuthNo auth required
ClientsClaude Desktop
Last updatedAug 11, 2026
10/10 checks healthy over the last 33d
Views2
Unique ViewsTotal visits recorded for this listing page on AllMCPs.
Installs0
Installs & Copy ActionsTotal times users copied install commands or configuration snippets for this server.
GitHub stars3
GitHub Star CountTotal stargazers on GitHub representing community popularity (3 stars).
Last commit1mo ago
Last Repository CommitThe most recent commit or push recorded for this server's GitHub repository.Last commit on Aug 11, 2026
68Quality signal: Great Ā· 68/100How this signal is calculated ā–¾
Server availability25/25
Verified ownership10/20
Documentation & tools30/30
Adoption & activity3/15
Community engagement0/10

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Scanned 24d ago via OSV.dev Ā· stella-mcp (PyPI)

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