# ai.byteask/embedded-docs

> Use this tool when you need to retrieve specific information from embedded documentation and firmware references to inform coding decisions. It solves problems of inefficient information gathering and inaccurate coding by providing direct access to primary sources. The tool takes page citations as input and returns relevant embedded documentation and firmware references as output.

Canonical page: https://skillsregistry.net/skills/ai-byteask-embedded-docs  
JSON: https://api.skillsregistry.net/v1/skills/ai-byteask-embedded-docs

## Description

Page-cited retrieval for embedded docs, datasheets, MISRA, CMSIS, and RTOS references.

## Trust

- **Trust score (0–1):** 0.90
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

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

## Source

- **Source listing:** [MCP Registry](https://registry.modelcontextprotocol.io/v0/servers/ai.byteask%2Fembedded-docs)
- **Repository:** <https://github.com/ByteAsk/ByteAsk-Embedded-MCP>

## Use it

MCP endpoint published by the skill: `https://mcp.byteask.ai/mcp`

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": "ai-byteask-embedded-docs"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/ai-byteask-embedded-docs` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/ai-byteask-embedded-docs/pull`

---
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