# JeffersonStats

> Use this tool when you need to perform in-depth statistical analysis, including descriptive statistics, hypothesis testing, and regression, to solve problems related to data interpretation and insight generation. It accepts various data inputs and returns detailed statistical outputs through a FastMCP-based API. Ideal for use in data-driven decision-making contexts where comprehensive statistical insights are required.

Canonical page: https://skillsregistry.net/skills/sharabhshukla-jeffersonstatsmcp  
JSON: https://api.skillsregistry.net/v1/skills/sharabhshukla-jeffersonstatsmcp

## Description

Enables comprehensive statistical analysis including descriptive statistics, hypothesis testing, regression, and more via a FastMCP-based API.

## Trust

- **Trust score (0–1):** 1.00
- **Verification tier:** verified
- **Last scanned:** 2026-09-19

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** other
- **Updated:** 2026-09-19

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/m737fgvzs2)
- **Repository:** <https://github.com/sharabhshukla/JeffersonStatsMCP>

## 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": "sharabhshukla-jeffersonstatsmcp"
    }
  }
}
```

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