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FreqBlog Music Metadata

com.freqblog/music-metadata · v1.1.0

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

MCPremoteno credentialsImages, video & audioAI & LLMScience & open data

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Last check

Reachable, 12 tools, protocol 2025-06-18 · checked 2026-10-17

Test & rating

B 80/100

What it does: 12 tools · 12 read, 0 write · Images, video & audio, E-commerce, AI & LLM

Test call get_recommendations: failed — tool error: Error executing tool get_recommendations: Provide either seed_tracks (1-5 catalog itunes_track_ids) or a track name (wit (961 ms)

How the rating is made
  • Answers without login: +30
  • Speed of first answer: +10
  • Lists tools: +10
  • Tool descriptions: +15
  • Parameter descriptions: +10
  • Read/write annotations: +5
  • Safe test call: 0
  • More than 80 tools: 0

Tested 2026-10-17. Fixed rules, no AI model. Grade A needs a successful real call.

Install

Remote URL
https://mcp.freqblog.com/mcp

Tools

12 tools listed at last check
  • 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
  • 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, n
  • 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. `
  • 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 a
  • 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 feature
  • 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 cat
  • 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
  • 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_
  • 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 ov
  • 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
  • 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 simil
  • 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_audi

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