# mcp-listenbrainz

> mcp-listenbrainz — pipeworx-io-mcp-listenbrainz. Use this tool when you need to manage and analyze music listening data, solving problems related to music metadata and user listening habits. It takes in music listening data as input and outputs insights and statistics, providing an interface for data analysis and visualization. Use it in contexts where music data analysis is required, such as music recommendation systems or user behavior studies.

Canonical page: https://skillsregistry.net/skills/pipeworx-io-mcp-listenbrainz  
JSON: https://api.skillsregistry.net/v1/skills/pipeworx-io-mcp-listenbrainz

## Description

ListenBrainz MCP.

## Trust

- **Trust score (0–1):** 0.99
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **License:** MIT
- **Updated:** 2026-09-28

## Source

- **Source listing:** [GitHub](https://github.com/pipeworx-io/mcp-listenbrainz)

## 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": "pipeworx-io-mcp-listenbrainz"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/pipeworx-io-mcp-listenbrainz` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/pipeworx-io-mcp-listenbrainz/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