# Koog Documentation MCP Server

> Use this tool when you need to efficiently search and retrieve specific information from large documentation sets. It solves the problem of manual browsing and information overload by providing semantic search capabilities over documentation using vector-based Retrieval-Augmented Generation (RAG). The tool takes in natural language questions as input and outputs relevant sections of documentation with context.

Canonical page: https://skillsregistry.net/skills/karel1980-koog-docs-helper-mcp  
JSON: https://api.skillsregistry.net/v1/skills/karel1980-koog-docs-helper-mcp

## Description

Enables semantic search over Koog documentation using vector-based RAG, allowing users to ask questions and retrieve relevant sections with context.

## Trust

- **Trust score (0–1):** 0.70
- **Verification tier:** verified
- **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/zw3100ox6g)
- **Repository:** <https://github.com/karel1980/koog-docs-helper-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": "karel1980-koog-docs-helper-mcp"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/karel1980-koog-docs-helper-mcp` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/karel1980-koog-docs-helper-mcp/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