Stella MCP vs Dingo

In-depth architectural comparison of the Stella MCP and Dingo 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.

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 Dingo 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: Rule-based data quality evaluation, LLM-based quality assessment, Rules and prompts discovery.

Explore Dingo Details

Feature & Specification Comparison

Specification	Stella MCP bradleylab Data Science Tools	Dingo DataEval Data Science Tools
Summary	Create, read, validate, and save Stella system dynamics models (.stmx files in XMILE format) for scientific simulation and modeling.	MCP server for the Dingo: a comprehensive data quality evaluation tool. Server Enables interaction with Dingo's rule-based and LLM-based evaluation capabilities and rules&prompts listing.
Category & Scope	Data Science Tools

Tools & Capabilities Breakdown

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).

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

{
  "mcpServers": {
    "dataeval-dingo": {
      "command": "uvx",
      "args": [
        "dingo-python"
      ]
    }
  }
}

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