# DevDocs

> Use this tool when you need to efficiently process and retrieve software documentation from various sources to enhance AI capabilities in software development workflows. It provides a Python-based interface for interacting with documentation, offering tools for processing, indexing, and content transformation. Ideal for tasks like code assistance, API exploration, or technical writing support, DevDocs simplifies access to technical documentation for AI models.

Canonical page: https://skillsregistry.net/skills/llmian-space-devdocs  
JSON: https://api.skillsregistry.net/v1/skills/llmian-space-devdocs

## Description

This DevDocs MCP implementation, developed by llmian-space, provides a Python-based interface for AI assistants to interact with software documentation. Built using libraries like Pydantic, Hypothesis, and Trio, it offers tools for processing, indexing, and retrieving documentation from various sources. The implementation focuses on efficient documentation handling, version management, and content transformation, making it easier for AI models to access and utilize technical documentation. It's particularly useful for enhancing AI capabilities in software development workflows, enabling tasks like code assistance, API exploration, or technical writing support without requiring deep knowledge of specific documentation formats or structures.

## 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/llmian-space-devdocs)
- **Repository:** <https://github.com/llmian-space/devdocs-mcp>

## 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": "llmian-space-devdocs"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/llmian-space-devdocs` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/llmian-space-devdocs/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