metamodel

MetaModel MCP Server

An MCP (Model Context Protocol) server that lets AI assistants use MetaModel's formula engine for certified computation. Turn published calculators, pricing tools, and engineering models into AI-callable tools — no hallucinated math.

All tools are read-only. This server fetches published project schemas and runs stateless computations. It never writes, modifies, or stores any data.

Quick Start

Remote (hosted) — easiest

No install. Add the URL as a custom connector:

https://www.metamodel.app/api/mcp

• Claude.ai / Claude Desktop: Settings → Connectors → Add custom connector → paste the URL
• Claude Code: claude mcp add --transport http metamodel https://www.metamodel.app/api/mcp

Works on web and mobile; no Node required. The hosted endpoint is stateless, read-only, and rate-limited.

Claude Desktop

Add to your Claude Desktop config (~/Library/Application Support/Claude/claude_desktop_config.json on macOS):

{
  "mcpServers": {
    "metamodel": {
      "command": "npx",
      "args": ["-y", "metamodel-mcp"]
    }
  }
}

Claude Code

claude mcp add metamodel -- npx -y metamodel-mcp

Other MCP Clients

Any MCP-compatible client can connect via stdio:

npx -y metamodel-mcp

Tools

metamodel_list_projects

Browse available calculators and engineering models. Returns project names, descriptions, publish tokens, and model names.

• Annotations: readOnlyHint: true

metamodel_get_schema

Discover inputs and outputs for a specific project. Returns model names, input parameters (with types, defaults, validation rules), output fields, and formulas.

• Annotations: readOnlyHint: true

Parameter	Type	Required	Description
token	string	Yes	Project publish token (from metamodel_list_projects)

metamodel_compute

Run a computation with input values. Send inputs once — they're auto-routed to the correct model by property name. Outputs from all models are returned, including cross-model cascading.

• Annotations: readOnlyHint: true

Parameter	Type	Required	Description
token	string	Yes	Project publish token
model	string	No	Target a specific model. When omitted, returns all models (recommended).
inputs	object	No	Input values as key-value pairs. Auto-routed to the correct model. Omitted inputs use defaults.

Examples

Example 1: List Available Projects

Prompt: "What calculators are available on MetaModel?"

Tool call: metamodel_list_projects()

Response (truncated):

{
  "projects": [
    {
      "token": "989bc6ae-e4d7-4585-8908-bfd03358043e",
      "name": "Deck Builder",
      "description": "Interactive deck builder with code-compliant sizing. Uses LOOKUP tables for beams, frost depths, and railing requirements.",
      "models": ["deck", "platformModel", "beamsModel", "postsModel", "railingModel", "summaryModel"]
    },
    {
      "token": "fdc5fbef-9d4b-46c3-b72d-1950e03d4bf4",
      "name": "Building Engineer",
      "description": "Complete building engineering calculator. Enter room dimensions to auto-size HVAC, electrical, and lighting systems with full cost estimation.",
      "models": ["room", "hvac", "electrical", "lighting", "costEstimator"]
    },
    {
      "token": "363c7753-ac4b-4de4-b1e7-e4536cb2f9bb",
      "name": "Life Expectancy Calculator",
      "description": "Estimate your life expectancy based on age, sex, and lifestyle factors.",
      "models": ["basics", "lifestyle", "results"]
    }
  ]
}

Example 2: Get Project Schema

Prompt: "What inputs does the Building Engineer calculator need?"

Tool call: metamodel_get_schema({ token: "fdc5fbef-9d4b-46c3-b72d-1950e03d4bf4" })

Response (truncated):

{
  "projectName": "Building Engineer",
  "models": [
    {
      "name": "room",
      "title": "Room Dimensions",
      "inputs": [
        { "name": "length", "type": "number", "defaultValue": 35.26 },
        { "name": "width", "type": "number", "defaultValue": 60 },
        { "name": "height", "type": "number", "defaultValue": 12 }
      ],
      "outputs": [
        { "name": "floorArea", "formula": "floorArea = length * width" },
        { "name": "volume", "formula": "volume = length * width * height" }
      ]
    },
    {
      "name": "hvac",
      "title": "HVAC Sizing",
      "inputs": [
        { "name": "climateZone", "defaultValue": "cold" },
        { "name": "btuFactor", "type": "number", "defaultValue": 25 }
      ],
      "outputs": [
        { "name": "btuRequired", "formula": "btuRequired = volume@room * btuFactor" },
        { "name": "tonnage", "formula": "tonnage = btuRequired / 12000" },
        { "name": "annualCost", "formula": "annualCost = tonnage * 120" }
      ]
    }
  ]
}

Note the cross-model references: volume@room means "use the volume output from the room model." MetaModel handles this cascading automatically.

Example 3: Run a Computation

Prompt: "Size the HVAC, electrical, and lighting for a 50×80 ft room with 14 ft ceilings"

Tool call: metamodel_compute({ token: "fdc5fbef-...", inputs: { length: 50, width: 80, height: 14 } })

Response:

{
  "models": {
    "room": {
      "outputs": { "floorArea": 4000, "volume": 56000, "wallArea": 3640 }
    },
    "hvac": {
      "outputs": { "btuRequired": 1400000, "tonnage": 116.7, "annualCost": 14000 }
    },
    "electrical": {
      "outputs": { "outletsNeeded": 304, "totalAmps": 456, "circuitCount": 23 }
    },
    "lighting": {
      "outputs": { "totalLumens": 201240, "fixtureCount": 51, "totalWattage": 2040 }
    },
    "costEstimator": {
      "outputs": {
        "hvacMaterial": 415917, "electricalMaterial": 18400,
        "lightingMaterial": 7650, "totalLabor": 89321, "grandTotal": 531288
      }
    }
  },
  "metadata": { "projectName": "Building Engineer", "evaluationMs": 7.1 }
}

One API call → room geometry, HVAC sizing, electrical load, lighting design, and full cost estimate. All computed from real formulas in ~7ms, not LLM-generated.

Development

To test against a local MetaModel instance:

# Clone and build
cd packages/mcp-server
npm install
npm run build

# Run with local URL
node dist/index.js --url http://localhost:3000

# Test with MCP Inspector
npx @modelcontextprotocol/inspector node dist/index.js --url http://localhost:3000

Privacy Policy

MetaModel's MCP server is stateless and read-only:

• No authentication required — all published projects are public
• No personal data collected — computations are anonymous
• No data stored — inputs are evaluated and discarded immediately
• No cookies or tracking — the server makes direct API calls to metamodel.app
• No third-party data sharing — results go only to the requesting client

Full privacy policy: https://www.metamodel.app/privacy

About MetaModel

MetaModel lets you build calculators, pricing tools, and engineering models with a spreadsheet-like formula language. Describe what you want, AI builds it, publish in seconds. Models become API-callable computation endpoints that any AI assistant can use via this MCP server.

License

MIT

Troubleshooting

• "Project not found or not published" — the token belongs to an unpublished or deleted project. Ask the project owner for a current publish token, or list what's available with metamodel_list_projects.
• Unknown input names — inputs are matched by property name. Call metamodel_get_schema first; it returns the exact input names, types, and defaults for the project.
• Inputs sent as a JSON string — pass inputs as a JSON object ({"width": 12}), not a stringified object. Stringified inputs fail with an "Unknown input" error naming a character index.
• Rate limits (hosted endpoint) — the hosted URL is rate-limited per client. For heavy use, run the npm package locally with your own network egress.
• Node version (local install) — the stdio server needs Node 18+.