# Llms.txt

> Use this tool when you need to enhance AI-assisted conversations with contextual information and integrate documentation directly into discussions. It provides a standardized interface for AI models to access and incorporate relevant documentation snippets, solving problems such as improved technical support and accurate code explanations. With inputs of AI model queries and outputs of contextual documentation snippets, it is ideal for use cases like technical support, code explanation, and educational dialogues.

Canonical page: https://skillsregistry.net/skills/secretiveshell-awesome-llms-txt  
JSON: https://api.skillsregistry.net/v1/skills/secretiveshell-awesome-llms-txt

## Description

This MCP server, developed by TerminalMan, provides integration with the Awesome-llms-txt project for adding documentation directly into conversations. Built with Python and leveraging the MCP framework, it offers a standardized interface for AI models to access and incorporate relevant documentation snippets. The implementation focuses on enhancing AI-assisted conversations with contextual information, enabling use cases such as improved technical support, more accurate code explanations, and enriched educational dialogues. By connecting AI models with curated documentation resources, this server allows for sophisticated information retrieval scenarios, particularly useful for applications and AI assistants that require quick access to specific documentation during interactions.

## Trust

- **Trust score (0–1):** 0.98
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-09-28

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/secretiveshell-awesome-llms-txt)
- **Repository:** <https://github.com/secretiveshell/mcp-llms-txt>

## 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": "secretiveshell-awesome-llms-txt"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/secretiveshell-awesome-llms-txt` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/secretiveshell-awesome-llms-txt/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