# LLMDoc

> Use this tool when you need to efficiently search and retrieve information from large documentation sources, such as llms.txt files. LLMDoc solves the problem of quickly finding relevant information by utilizing hybrid two-stage retrieval and automatic background refresh, providing up-to-date results. It takes in search queries as input and outputs relevant documentation sources, making it ideal for use cases where rapid access to accurate information is crucial.

Canonical page: https://skillsregistry.net/skills/bigbag-llmdoc  
JSON: https://api.skillsregistry.net/v1/skills/bigbag-llmdoc

## Description

MCP server for semantic search across llms.txt documentation sources, with hybrid two-stage retrieval and automatic background refresh.

## Trust

- **Trust score (0–1):** 0.69
- **Verification tier:** scanned
- **Last scanned:** 2026-08-31

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-08-31

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/atjmj3atq3)
- **Repository:** <https://github.com/bigbag/llmdoc>

## 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": "bigbag-llmdoc"
    }
  }
}
```

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