@mob999/cube_mcp

Cube.js TypeScript MCP Server

This is a standalone Model Context Protocol (MCP) server for Cube.js, written in TypeScript using the official @cubejs-client/core SDK.

It provides advanced AI assistants (like Claude, Cursor, etc.) with semantic layer visibility and multi-dimensional querying capabilities over your data.

Features

• discover_entities: Introspects the Cube.js metadata (/meta) and explains the available Cubes, Dimensions, and Measures to the LLM.
• execute_query: Executes semantic queries (/load) with support for Cube query fields like filters, sorting, time dimensions, pagination, timezone, and result truncation.

Prerequisites

• Node.js (v18 or higher recommended)
• A running instance of Cube.js

Quick Start

You can run the published MCP server directly without installing it manually: ``bash npx -y @mob999/cube_mcp ``

Local Development & Build

1. Install dependencies:

   npm install

1. Build the TypeScript source:

   npm run build

This compiles the TypeScript code into the dist/ directory.

Development & Testing

• Run Tests: npm test
• Lint Code: npm run lint

Query Features

execute_query supports:

• measures
• dimensions
• filters
• timeDimensions
• segments
• limit
• rowLimit
• offset
• order
• timezone
• renewQuery
• ungrouped
• responseFormat
• total

Example:

{
  "entity_name": "Components",
  "measures": ["Components.count"],
  "dimensions": ["Components.id"],
  "timeDimensions": [
    {
      "dimension": "Components.createdAt",
      "granularity": "day",
      "dateRange": ["2026-01-01", "2026-01-31"]
    }
  ],
  "order": [
    { "member": "Components.count", "direction": "desc" },
    { "member": "Components.id", "direction": "asc" }
  ],
  "limit": 100,
  "rowLimit": 500,
  "offset": 0,
  "timezone": "UTC",
  "responseFormat": "compact",
  "total": true
}

Configuration

By default, the server expects your Cube.js API to be available at http://localhost:4000/cubejs-api/v1.

You can override this by setting the CUBEJS_API_URL environment variable.

To integrate this semantic layer into Cursor or any other MCP-compatible IDE/Agent, configure it as a stdio tool.

Example mcp.json / Client Configuration:

{
  "mcpServers": {
    "CubeSemanticLayer": {
      "command": "npx",
      "args": ["-y", "@mob999/cube_mcp"],
      "env": {
        "CUBEJS_API_URL": "http://localhost:4000/cubejs-api/v1"
      }
    }
  }
}

Note: The -y flag allows npx to automatically download and run the package without prompting for confirmation.