What is the key difference between Stella MCP and Fermat MCP?

Stella MCP belongs to the Data Science Tools category with local stdio execution, while Fermat MCP belongs to the Data Science Tools category with local stdio execution.

How do I install Stella MCP or Fermat MCP in Claude Desktop or Cursor?

Copy the mcpServers JSON configuration snippet provided on this page into your claude_desktop_config.json or ~/.cursor/mcp.json file and restart your AI client.

Are Stella MCP and Fermat MCP free or paid?

Stella MCP operates under a Free / Open Source model (No auth required). Fermat MCP operates under a Free / Open Source model (No auth required).

Which MCP server has more tools and community activity?

Stella MCP lists 42 tools with 2 views and 3 GitHub stars. Fermat MCP lists 5 tools with 3 views and 20 GitHub stars.

Can I use both Stella MCP and Fermat MCP together in the same MCP host?

Yes! MCP hosts like Claude Desktop, Cursor, Windsurf, Cline, and VS Code support configuring multiple servers under the mcpServers object simultaneously.

Side-by-Side Model Context Protocol Comparison

Stella MCP vs Fermat MCP

In-depth architectural comparison of the Stella MCP and Fermat MCP MCP servers. Compare execution transports, security boundaries, tool capabilities, quality scores, and ready-to-paste client installation snippets for Claude, Cursor, Windsurf, and VS Code.

At a Glance & Executive Verdict

Stella MCP

Data Science Tools · Local stdio

Quality: 57/100 (Good) | Auth: No auth required

Fermat MCP

Data Science Tools · Local stdio

Quality: 57/100 (Good) | Auth: No auth required

Verdict Summary: Choose Stella MCP if you need specialized Data Science Tools tools running via a local process. Choose Fermat MCP if your workspace requires Data Science Tools integration with local subprocess execution. Both servers can be configured concurrently in your client's mcpServers manifest.

Which MCP Server Should You Choose?

Choose Stella MCP when:

You need dedicated capabilities in the Data Science Tools domain.
You prefer local stdio subprocess transport architecture.
Your security boundary fits: No auth required (Free / Open Source).
Primary tools included: create_model, build_model, add_variables.

Explore Stella MCP Details

Choose Fermat MCP when:

You need dedicated capabilities in the Data Science Tools domain.
You prefer local stdio subprocess transport architecture.
Your security boundary fits: No auth required (Free / Open Source).
Primary tools included: NumPy numerical operations, SymPy symbolic algebra and calculus, Linear algebra and matrix functions.

Explore Fermat MCP Details

Feature & Specification Comparison

Specification	Stella MCP bradleylab Data Science Tools	Fermat MCP abhiphile Data Science Tools
Summary	Create, read, validate, and save Stella system dynamics models (.stmx files in XMILE format) for scientific simulation and modeling.	The ultimate math engine unifying SymPy, NumPy & Matplotlib in one powerful server. Perfect for developers & researchers needing symbolic algebra, numerical computing, and data visualization.
Category & Scope	Data Science Tools

Tools & Capabilities Breakdown

Stella MCP Tools (42)

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

Ready-to-Paste Client Configurations

Paste either (or both) of these JSON server blocks into your client config file (e.g. claude_desktop_config.json or ~/.cursor/mcp.json).

Stella MCP Configuration

mcpServers (Claude Desktop / Cursor)

{
  "mcpServers": {
    "bradleylab-stella-mcp": {
      "command": "uvx",
      "args": [
        "stella-mcp"
      ]
    }
  }
}

Fermat MCP Configuration

mcpServers (Claude Desktop / Cursor)

{
  "mcpServers": {
    "abhiphile-fermat-mcp": {
      "command": "npx",
      "args": [
        "-y",
        "@smithery/cli"
      ]
    }
  }
}

Frequently Asked Questions

Stella MCP is categorized under Data Science Tools and uses a local stdio subprocess. In contrast, Fermat MCP belongs to Data Science Tools using local stdio subprocess. Select Stella MCP when you need capabilities focused on data science tools and Fermat MCP when you require tools for data science tools.

More alternatives to Stella MCP More alternatives to Fermat MCP Data Science Tools category hub Canonical compare URL