# DataRaum

> Use this tool when you need to accelerate AI-driven data analytics by leveraging pre-computed metadata context. DataRaum solves problems related to data discovery, filtering, and prioritization, enabling faster and more accurate insights. It takes in data sources and outputs contextualized metadata, ideal for use cases where data complexity and volume hinder efficient analysis.

Canonical page: https://skillsregistry.net/skills/io-github-dataraum-dataraum  
JSON: https://api.skillsregistry.net/v1/skills/io-github-dataraum-dataraum

## Description

Pre-computed metadata context engine for AI-driven data analytics

## Trust

- **Trust score (0–1):** 0.70
- **Verification tier:** unverified

## Facts

- **Version:** 0.2.1
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** data-analytics
- **Updated:** 2026-04-19

## Source

- **Source listing:** [MCP Registry](https://registry.modelcontextprotocol.io/v0/servers/io.github.dataraum%2Fdataraum)
- **Repository:** <https://github.com/dataraum/dataraum>

## 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": "io-github-dataraum-dataraum"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/io-github-dataraum-dataraum` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/io-github-dataraum-dataraum/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