# PyRag

> PyRag — nateislas-pyrag. Use this tool when you need to access current and comprehensive Python library documentation to streamline AI coding assistant development. PyRag solves the problem of outdated examples and incorrect information by providing up-to-date documentation through its MCP server interface. It takes in git repository data and outputs accurate library information, making it ideal for use cases where reliable coding references are crucial.

Canonical page: https://skillsregistry.net/skills/nateislas-pyrag  
JSON: https://api.skillsregistry.net/v1/skills/nateislas-pyrag

## Description

PyRag is an MCP (Model Context Protocol) server that provides AI coding assistants with access to current, comprehensive Python library documentation. It eliminates the frustration of outdated examples and wrong information that slows down development.

## Trust

- **Trust score (0–1):** 0.00
- **Verification tier:** scanned
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **License:** MIT
- **Updated:** 2026-09-28

## Source

- **Source listing:** [GitHub](https://github.com/nateislas/PyRag)

## 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": "nateislas-pyrag"
    }
  }
}
```

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