# outline-mcp

> outline-mcp — ynishi-outline-mcp. Use this tool when you need to organize and manage complex knowledge bases in a tree-structured format, enabling persistent and editable storage for LLM sessions. It solves problems of knowledge fragmentation and loss, providing a centralized hub for browsing, annotating, and injecting context into AI models. With inputs of raw knowledge data and outputs of structured, editable trees, use outline-mcp in applications requiring collaborative, dynamic knowledge management.

Canonical page: https://skillsregistry.net/skills/ynishi-outline-mcp  
JSON: https://api.skillsregistry.net/v1/skills/ynishi-outline-mcp

## Description

Tree-structured knowledge base as an MCP server, giving LLM sessions a persistent, editable knowledge tree with browsing, annotation, and context injection.

## Trust

- **Trust score (0–1):** 0.31
- **Verification tier:** scanned
- **Last scanned:** 2026-08-29

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-08-29

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/gmdoc9xwng)
- **Repository:** <https://github.com/ynishi/outline-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": "ynishi-outline-mcp"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/ynishi-outline-mcp` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/ynishi-outline-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