# MCP Analyst

> Use this tool when you need to analyze large local datasets without uploading them, as it enables efficient processing of CSV or Parquet files. The MCP Analyst handles bigger datasets, solving data upload limitations and processing constraints. It takes local CSV or Parquet files as input and provides analyzed data as output, ideal for use cases requiring offline data analysis or handling sensitive information.

Canonical page: https://skillsregistry.net/skills/unravel-team-mcp-analyst  
JSON: https://api.skillsregistry.net/v1/skills/unravel-team-mcp-analyst

## Description

Enables Claude to analyze local CSV or Parquet files, handling larger datasets without uploading full files.

## Trust

- **Trust score (0–1):** 0.70
- **Verification tier:** verified
- **Last scanned:** 2026-09-01

## Facts

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

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/v90v2tanbc)
- **Repository:** <https://github.com/unravel-team/mcp-analyst>

## 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": "unravel-team-mcp-analyst"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/unravel-team-mcp-analyst` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/unravel-team-mcp-analyst/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