# RefineDataMCP

> Use this tool when you need to efficiently process and prepare large datasets for AI model training, anonymizing sensitive information and handling big data with ease. It solves problems related to data quality, security, and scalability, providing a robust interface for inputting raw data and outputting refined, anonymized datasets. Ideal for use cases involving massive data volumes, RefineDataMCP streamlines data preparation with Polars and DuckDB.

Canonical page: https://skillsregistry.net/skills/enesp4rl4k-refinedata-mcp  
JSON: https://api.skillsregistry.net/v1/skills/enesp4rl4k-refinedata-mcp

## Description

Provides data preparation, anonymization, and processing tools for AI agents, handling big data with Polars and DuckDB.

## Trust

- **Trust score (0–1):** 0.59
- **Verification tier:** scanned
- **Last scanned:** 2026-09-01

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-09-01

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/rovykl9yyk)
- **Repository:** <https://github.com/Enesp4rl4k/refinedata-mcp>

## 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": "enesp4rl4k-refinedata-mcp"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/enesp4rl4k-refinedata-mcp` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/enesp4rl4k-refinedata-mcp/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