# FreqBlog Music Metadata

> Use this tool when you need to analyze audio features of music tracks, such as BPM, key, mood, and genre, to enhance music recommendation systems, playlists, or audio-based applications. It solves problems related to music classification, recommendation, and discovery by providing detailed metadata for real tracks. The tool takes audio tracks as input and outputs corresponding metadata, making it a suitable replacement for Spotify audio features in various music-related projects.

Canonical page: https://skillsregistry.net/skills/com-freqblog-music-metadata  
JSON: https://api.skillsregistry.net/v1/skills/com-freqblog-music-metadata

## Description

Audio features + harmonic set-building for tracks by name/ISRC. Spotify audio-features replacement.

## Trust

- **Trust score (0–1):** 0.70
- **Verification tier:** unverified

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** media
- **Updated:** 2026-08-18

## Source

- **Source listing:** [MCP Registry](https://registry.modelcontextprotocol.io/v0/servers/com.freqblog%2Fmusic-metadata)

## Use it

MCP endpoint published by the skill: `https://mcp.freqblog.com/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": "com-freqblog-music-metadata"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/com-freqblog-music-metadata` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/com-freqblog-music-metadata/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