# RAGDocs (Vector Documentation Search)

> Use this tool when you need to enhance AI responses with relevant documentation context or provide semantic search capabilities for stored documentation. It solves problems related to information retrieval and contextual understanding by indexing and retrieving documentation from vector databases. The tool takes in URLs, documentation sources, and embedding providers as inputs and outputs relevant search results and extracted URLs.

Canonical page: https://skillsregistry.net/skills/jumasheff-ragdocs-vector-documentation-search  
JSON: https://api.skillsregistry.net/v1/skills/jumasheff-ragdocs-vector-documentation-search

## Description

MCP-RAGDocs is a server implementation that provides semantic documentation search and retrieval using vector databases to augment LLM capabilities. Developed by hannesrudolph and forked by jumasheff, it enables AI assistants to search through stored documentation, extract URLs from web pages, manage documentation sources, and process queues of URLs for indexing. The server uses Qdrant for vector storage and supports multiple embedding providers including Ollama and OpenAI, making it particularly valuable for enhancing AI responses with relevant documentation context without requiring users to switch between interfaces.

## Trust

- **Trust score (0–1):** 0.92
- **Verification tier:** verified
- **Last scanned:** 2026-09-19

## Facts

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

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/jumasheff-ragdocs-vector-documentation-search)
- **Repository:** <https://github.com/jumasheff/mcp-ragdoc-fork>

## 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": "jumasheff-ragdocs-vector-documentation-search"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/jumasheff-ragdocs-vector-documentation-search` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/jumasheff-ragdocs-vector-documentation-search/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