# Online Kommentar

> Use this tool when you need to access Swiss legal commentary and analysis programmatically, or automate searches for specific legislative acts and commentaries. It solves problems of manual data retrieval and provides filtered search results and detailed commentary information through its REST API. Ideal for legal professionals, researchers, and AI assistants requiring efficient access to Online Kommentar's database.

Canonical page: https://skillsregistry.net/skills/onlinekommentar  
JSON: https://api.skillsregistry.net/v1/skills/onlinekommentar

## Description

MCP server implementation that provides access to the Online Kommentar legal commentary database through its REST API. Built with TypeScript and the MCP SDK, it exposes two core tools: searching for legal commentaries with filters for language, legislative acts, and sorting options, and retrieving detailed commentary information by ID including authors, editors, publication dates, and content. Designed for legal professionals, researchers, and AI assistants who need programmatic access to Swiss legal commentary and analysis without manually navigating the Online Kommentar website.

## 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:** database
- **Updated:** 2026-09-28

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/onlinekommentar)
- **Repository:** <https://github.com/self-tech-labs/onlinekommentar-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": "onlinekommentar"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/onlinekommentar` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/onlinekommentar/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