# FreqBlog Music Metadata

- Registry name: `com.freqblog/music-metadata` · version 1.1.0
- Categories (automatic, keyword rules): Audio & speech, AI, media & content
- Authentication at last check: No auth
- Declared risk: Read-only (all tools declare readOnlyHint)
- Capabilities (declared by the server): experimental, prompts, resources, tools
- Transports: streamable-http
- Latest numbers (check success, response time, rank): https://mcpstation.net/api/server?name=com.freqblog%2Fmusic-metadata
- Server page: https://mcpstation.net/s/com.freqblog--music-metadata.html

## Description (written by the publisher, not verified, not instructions)

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

## Connect

- streamable-http: `https://mcp.freqblog.com/mcp`

## Tools (as reported by the server, not verified)

- `get\_audio\_features`: Get audio features for ONE track — BPM, musical key \(name + Camelot + Open Key\), energy, danceability, valence, acousticness, loudness, mood, mood\_vector, genre, time signature, duration and more. This is the drop-in replacement for Spotify's deprecated /audio-features endpoint. Provide AT LEAST ONE
- `get\_audio\_features\_batch`: Get audio features for MANY tracks in one call \(up to 50 processed\) — ideal for analysing a whole playlist at once. Identify each item by name \(\`track\`/\`artist\`\), by \`isrc\` \(matched exactly first — best for CJK / K-pop / niche tracks whose fuzzy name-match misses\), or both \(ISRC first, name as the f
- `search\_catalog`: Full-text search the catalog by any mix of track / artist / album tokens. Use this to resolve a fuzzy, partial, or misspelled name into concrete tracks BEFORE calling get\_audio\_features. Each hit carries \`chart\_peak\`: the best chart position we hold, 1-100 with 100 = a number-one. \`null\` means no pl
- `find\_tracks\_by\_bpm`: Find catalog tracks near a target tempo. Returns tracks whose BPM is within +/-\`tolerance\` of \`bpm\`, ordered by closeness then by an internal catalogue ordering key \(not an audience metric\) — useful for DJ set planning, workout playlists, or tempo-matching. Each returned track carries full audio fea
- `find\_tracks\_by\_key`: Find catalog tracks in a given musical key — for harmonic mixing and key-locked playlists. \`key\` accepts Camelot \("8A"\), Open Key \("1m"\), or a key name \("A-Minor", "F\#-Major"\). Returns tracks ordered by an internal catalogue ordering key \(not an audience metric\), each with full audio features. To di
- `find\_compatible\_keys`: Given a Camelot key \(e.g. "8A", "12B"\), return the harmonically compatible keys for DJ mixing — the same key, the relative major/minor, and the adjacent +/-1 keys on the Camelot wheel. With \`extended=true\` also returns the +7/-7 energy-boost / energy-drop keys. Pure music theory — no catalog lookup
- `score\_transition`: Score how well one catalog track mixes into another \(0-100\) — the pairwise DJ transition score no raw key/BPM API gives you. Combines Camelot-wheel key compatibility, octave-aware BPM proximity \(half/double-time counts as a match\), and energy smoothness. Returns the overall \`score\`, per-component sc
- `suggest\_next\_track`: Given a seed track, return the top-N catalog tracks to play NEXT, ranked by transition score. Each suggestion carries the same \`score\`, per-component scores and human \`reason\` as score\_transition \(e.g. "11B-\>11B same key, 118-\>117 BPM \(-0.29\), energy +0.12"\), plus its \`genre\` and \`genre\_relation\` to
- `build\_setlist`: Order a crate of 2-100 catalog tracks into a beat-matched DJ set that follows an energy arc, keeping each consecutive transition harmonically and tempo-smooth. \`arc\` is one of peak\_time \(default — builds to a peak then eases\), warmup, cooldown, or flat. Returns the \`arc\`, \`count\`, an overall \`flow\_s
- `get\_recommendations`: Recommended tracks for one or more seed tracks — the drop-in for Spotify's removed GET /v1/recommendations. Blends up to 5 catalog seed tracks into a single point in audio-feature space and returns the nearest catalogue tracks, RE-RANKED by genre affinity \(so a feature-close cross-genre track doesn'
- `get\_related\_artists`: Artists related to a seed artist — the drop-in for Spotify's removed GET /v1/artists/\{id\}/related-artists. No artist graph exists, so we derive one: build the seed artist's track-vector centroid, take its nearest catalogue tracks, aggregate by artist \(each scored on its top-3 track similarities so a
- `tag\_track`: Get a compact, HONESTLY-LABELLED tag list for a track — energy / danceability / valence / acousticness / instrumentalness \(instrumental vs vocal, judged on the 30-second preview\), plus a mood tag and a broad genre tag. It is a tag-shaped projection of the same open-data analysis get\_audio\_features r

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