# Cube

> Use this tool when you need to interact with semantic data layers and simplify access to complex data structures. It solves problems such as automated data analysis, natural language querying of business metrics, and AI-assisted data exploration by providing a Python-based interface to Cube.dev's REST API. The tool takes in queries and requests, and outputs data and metadata, making it ideal for organizations looking to leverage AI agents with their existing Cube deployments.

Canonical page: https://skillsregistry.net/skills/isaacwasserman-cube  
JSON: https://api.skillsregistry.net/v1/skills/isaacwasserman-cube

## Description

This MCP server, developed by Isaac Wasserman, interfaces with Cube.dev's REST API to enable AI agents to interact with semantic data layers. Built with Python and utilizing the Model Context Protocol SDK, it provides tools for querying and describing data available in Cube deployments. The implementation focuses on simplifying access to complex data structures, offering functionality to read data and retrieve metadata. It's particularly useful for organizations looking to leverage their existing Cube semantic layers with AI agents, enabling use cases such as automated data analysis, natural language querying of business metrics, and AI-assisted data exploration without directly dealing with Cube's API complexities.

## Trust

- **Trust score (0–1):** 0.94
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** devops-ci
- **Updated:** 2026-09-28

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/isaacwasserman-cube)
- **Repository:** <https://github.com/isaacwasserman/mcp_cube_server>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "isaacwasserman-cube"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/isaacwasserman-cube` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/isaacwasserman-cube/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt