# stats-mcp

> stats-mcp — mukundakatta-stats-mcp. Use this tool when you need to calculate descriptive statistics for a numeric array, solving problems such as data analysis and summary. It takes a numeric array as input and outputs statistical measures, providing a simple interface for data exploration. Ideal for use cases requiring quick insights into dataset characteristics, such as mean, median, and standard deviation calculations.

Canonical page: https://skillsregistry.net/skills/mukundakatta-stats-mcp  
JSON: https://api.skillsregistry.net/v1/skills/mukundakatta-stats-mcp

## Description

MCP server: descriptive statistics over a numeric array.

## Trust

- **Trust score (0–1):** 0.65
- **Verification tier:** scanned
- **Last scanned:** 2026-09-01

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **Category:** other
- **Updated:** 2026-09-21

## Source

- **Source listing:** [GitHub](https://github.com/MukundaKatta/stats-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": "mukundakatta-stats-mcp"
    }
  }
}
```

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