MCP Cube Server

v1.0.0Databasesstable

MCP Server for Interacting with Cube Semantic Layers

mcp-cube-servermcpai-integration
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What is MCP Cube Server?

MCP Cube Server is a Model Context Protocol (MCP) server that allows AI assistants like Claude, Cursor, and VS Code to mcp server for interacting with cube semantic layers

MCP Server for Interacting with Cube Semantic Layers

This server falls under the Databases category on MCPgee, the world's largest MCP server directory with 33,000+ servers.

Features

  • MCP Server for Interacting with Cube Semantic Layers

Use Cases

Query Cube semantic layers
AI-assisted analytics
isaacwasserman

Maintainer

LicenseGPL-3.0
Languagepython
Versionv1.0.0
UpdatedApr 27, 2026
Statushealthy
Maintenanceactive

Works with

ClaudeOpenAIwindowsmacoslinux

Installation

Manual Installation

npx mcp-cube-server

Configuration

Configuration Details

Config File

claude_desktop_config.json

Performance

Response Metrics

Response Time< 200ms
ThroughputMedium

Resource Usage

Memory UsageLow
CPU UsageLow

How to Set Up and Use MCP Cube Server

MCP Cube Server is a Python MCP server that connects AI assistants to Cube semantic layer deployments, enabling natural-language queries over your business data. It exposes tools for querying the Cube REST API and describing available data models, returning results in YAML and JSON formats. Data analysts and engineers can use it to let AI models explore and query Cube-defined metrics without writing raw SQL.

Prerequisites

  • Python 3.10 or higher installed
  • A running Cube deployment (cloud or self-hosted) with REST API access
  • Cube REST API endpoint URL and a valid API token
  • uv or pip package manager installed
  • An MCP client such as Claude Desktop
1

Clone the repository

Clone the mcp_cube_server repository from GitHub.

git clone https://github.com/isaacwasserman/mcp_cube_server.git
cd mcp_cube_server
2

Install the package

Install the Python package and its dependencies using pip or uv.

pip install -e .
3

Obtain your Cube API credentials

Log in to your Cube deployment, navigate to the API section, and copy the REST API base URL and your API token. You will need these for the MCP client configuration.

4

Configure your MCP client

Add the MCP Cube Server to your client's configuration with your Cube API URL and token passed as environment variables or arguments.

5

Test the connection

Ask your MCP client to describe the available data in your Cube deployment. The describe_data tool will return a list of available cubes and their dimensions/measures.

MCP Cube Server Examples

Client configuration

Add MCP Cube Server to Claude Desktop pointing to your Cube deployment.

{
  "mcpServers": {
    "cube": {
      "command": "python",
      "args": ["-m", "mcp_cube_server"],
      "env": {
        "CUBE_API_URL": "https://your-cube-deployment.cubecloudapp.dev/cubejs-api/v1",
        "CUBE_API_TOKEN": "your-cube-api-token"
      }
    }
  }
}

Prompts to try

Example prompts to explore and query your Cube semantic layer.

- "Describe all available data in my Cube deployment."
- "Query total orders by product category for the last 30 days."
- "What metrics and dimensions are available in the Sales cube?"
- "Get daily revenue for the past week and format it as a table."

Troubleshooting MCP Cube Server

Authentication errors when querying the Cube REST API

Verify that CUBE_API_TOKEN is set correctly and that the token has not expired. In Cube Cloud, regenerate the token from the API Credentials section if needed.

read_data returns no results for a valid query

Use describe_data first to confirm the cube name, measure names, and dimension names are correct. Cube's REST API is case-sensitive and requires exact member names as defined in your schema.

Server fails to start with ModuleNotFoundError

Ensure the package was installed in the same Python environment used to run the server. Run 'pip install -e .' inside the cloned directory and verify with 'python -c "import mcp_cube_server"'.

Frequently Asked Questions about MCP Cube Server

What is MCP Cube Server?

MCP Cube Server is a Model Context Protocol (MCP) server that mcp server for interacting with cube semantic layers It connects AI assistants to external tools and data sources through a standardized interface.

How do I install MCP Cube Server?

Follow the installation instructions on the MCP Cube Server GitHub repository. Clone the repo, install dependencies, and add the server config to your AI client.

Which AI clients work with MCP Cube Server?

MCP Cube Server works with all major MCP-compatible AI clients including Claude Desktop, Claude Code, Cursor, VS Code (GitHub Copilot), Windsurf, and Cline.

Is MCP Cube Server free to use?

Yes, MCP Cube Server is open source and available under the GPL-3.0 license. You can use it freely in both personal and commercial projects.

Browse More Databases MCP Servers

Explore all databases servers available in the MCPgee directory. Each server includes setup guides for Claude, Cursor, and VS Code.

Quick Config Preview

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

Add this to your claude_desktop_config.json or .cursor/mcp.json

Read the full setup guide →

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