FreqBlog Music Metadata
Audio features + harmonic set-building for tracks by name/ISRC. Spotify audio-features replacement.
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Calidad y seguridad
Basado en el análisis automatizado de las definiciones de herramientas y el cumplimiento del protocolo.
Costo de contexto
Este es el número aproximado de tokens que se consumen cada vez que las herramientas del servidor se cargan en el contexto de un modelo. Los recuentos más altos reducen la atención disponible para otras tareas.
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Agrega esto a tu archivo `claude_desktop_config.json`:
{
"mcpServers": {
"music-metadata": {
"url": "https://mcp.freqblog.com/mcp"
}
}
}Puntos de conexión remotos
https://mcp.freqblog.com/mcpstreamable-httpQué puede hacer
Inventario de herramientas
Herramientas (12)
🟢get_audio_features(track, artist, isrc, mbid, spotify_id)
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 identifier — if you know several, send them all rather than choosing; they resolve by precedence (`track` > `isrc` > `mbid` > `spotify_id`) and the rest are ignored: - `track` (optionally with `artist`) — e.g. track="Blinding Lights", artist="The Weeknd". - `isrc` — e.g. "USUM71900001". - `mbid` — a MusicBrainz recording UUID. - `spotify_id` — a Spotify track ID, URI, or URL (resolved per request by reading the track's title from Spotify's public embed page and matching it against our catalogue — no Spotify IDs are stored; ambiguous titles miss rather than guess — prefer `track`/`isrc` for full coverage). Returns a JSON object of features. Some feature fields may be null for tracks resolved via the fallback catalogs (only audio-derived values are present for fully analysed tracks). VALUES are FreqBlog's own analysis, NOT on Spotify's scale: energy, danceability and valence are on our own raw scale (derive thresholds from our values, don't copy Spotify-tuned ones); acousticness is the AcousticBrainz classifier where available, else our estimate (being replaced by a new model since 2026-09-27); instrumentalness, speechiness and liveness are currently null for catalogue tracks. If a track name is not yet in the catalog, the API holds the request during the on-demand ingest and usually returns the fully analysed track inline in this same call; only if the ingest runs long does it fall back to a queued response you can re-poll shortly (~15s). If the track turns out not to be on any streaming source we can analyse, you get a definitive not-found instead — that verdict is terminal for ~7 days, so don't retry it. If you only have a fuzzy or partial name, call search_catalog first to find the exact track.
Esquema de entrada
{
"type": "object",
"properties": {
"track": {
"anyOf": [
{
"type": "string"
},
{
"type": "null"
}
],
"default": null,
"description": "Track title. Use with `artist` when known. Supply AT LEAST ONE of track/isrc/mbid/spotify_id. Sending several is fine — they resolve by precedence (track > isrc > mbid > spotify_id) and the rest are ignored.",
"title": "Track"
},
"artist": {
"anyOf": [
{
"type": "string"
},
{
"type": "null"
}
],
"default": null,
"description": "Artist name. Only used with `track`; required when the title is <=2 characters.",
"title": "Artist"
},
"isrc": {
"anyOf": [
{
"type": "string"
},
{
"type": "null"
}
],
"default": null,
"description": "ISRC, e.g. 'USUM71900001'.",
"title": "Isrc"
},
"mbid": {
"anyOf": [
{
"type": "string"
},
{
"type": "null"
}
],
"default": null,
"description": "MusicBrainz recording ID (UUID). The precise key when there is no ISRC, e.g. pre-1986 recordings.",
"title": "Mbid"
},
"spotify_id": {
"anyOf": [
{
"type": "string"
},
{
"type": "null"
}
],
"default": null,
"description": "Spotify track ID, 'spotify:track:...' URI, or open.spotify.com URL. Resolved per request by reading the track's title from Spotify's public embed page and matching it against our catalogue (no Spotify IDs are stored) — a title several artists share is ambiguous and misses rather than guessing; prefer track (+artist) or isrc.",
"title": "Spotify Id"
}
},
"title": "get_audio_featuresArguments"
}Esquema de salida
{
"type": "object",
"additionalProperties": true,
"title": "get_audio_featuresDictOutput"
}🟢get_audio_features_batch(tracks)
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 fallback). One bad entry never fails the batch. Items beyond the 50-per-call cap come back with `found: false` and `backfill_status: "over_limit"`; an item missing BOTH `track` and `isrc` comes back `"invalid_no_query"`. Neither is processed or charged — the response's `skipped` field counts them, so split a long list into calls of <=50 and resubmit any skipped rows. Returns counts (`found` / `not_found` / `skipped`) plus a per-track `results` array, where each entry's `result` is the same feature object as get_audio_features (or null when not found), and `isrc` is echoed back. An item is billed only when it returns features or queues an on-demand ingest; an ISRC/name with no match anywhere is free. A track you queue and then collect costs ONE unit, not two — the call that collects it is free. For a single track, use get_audio_features.
Esquema de entrada
{
"type": "object",
"properties": {
"tracks": {
"description": "List of {track?, artist?, isrc?} objects. Up to 50 are processed per call; any extra (up to 200 accepted) come back skipped. Each item should carry `track` or `isrc`.",
"items": {
"$ref": "#/$defs/TrackQuery"
},
"maxItems": 200,
"minItems": 1,
"title": "Tracks",
"type": "array"
}
},
"required": [
"tracks"
],
"$defs": {
"TrackQuery": {
"description": "One track to look up by name and/or ISRC. Supply `track` or `isrc` (or both); an item\ncarrying neither is skipped by the batch tool (`invalid_no_query`), not an error.",
"properties": {
"track": {
"anyOf": [
{
"maxLength": 200,
"type": "string"
},
{
"type": "null"
}
],
"default": null,
"description": "Track title. Supply this OR `isrc` (or both — ISRC is matched exactly first, the name is the fallback).",
"title": "Track"
},
"artist": {
"anyOf": [
{
"maxLength": 200,
"type": "string"
},
{
"type": "null"
}
],
"default": null,
"description": "Artist name (optional, improves name-match accuracy)",
"title": "Artist"
},
"isrc": {
"anyOf": [
{
"maxLength": 15,
"type": "string"
},
{
"type": "null"
}
],
"default": null,
"description": "ISRC, e.g. 'USUM71900001' (hyphens optional). Matched exactly first — resolves CJK/K-pop/niche tracks whose fuzzy name-match misses. Supply this OR `track`.",
"title": "Isrc"
}
},
"title": "TrackQuery",
"type": "object"
}
},
"title": "get_audio_features_batchArguments"
}Esquema de salida
{
"type": "object",
"additionalProperties": true,
"title": "get_audio_features_batchDictOutput"
}🟢search_catalog(q, limit)
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 placement we hold — treat that as UNKNOWN, not unpopular, and note it is NOT an audience-size figure. Coverage is Billboard year-end only so far. Returns lightweight stubs (itunes_track_id, track_name, artist_name, album, etc.) ranked by relevance — NOT audio features. Take the best match's track_name + artist_name and pass them to get_audio_features, or reuse its itunes_track_id as a `track_id` seed for discovery tools. ⚠ Each hit carries a `seedable` boolean. Only a hit with `seedable: true` can be used as a seed for get_recommendations / suggest_next_track / build_setlist / score_transition — those work off the similarity index, which holds only tracks we have analysed, and about a quarter of the catalogue is not analysed yet. **Prefer the highest-ranked hit with `seedable: true`.** Seeding with a `seedable: false` id returns a 404; if that track is the one you want, call get_audio_features on it first to queue analysis, then retry.
Esquema de entrada
{
"type": "object",
"properties": {
"q": {
"description": "Search query — any mix of artist / track / album tokens.",
"maxLength": 200,
"minLength": 1,
"title": "Q",
"type": "string"
},
"limit": {
"default": 10,
"description": "Max results (default 10).",
"maximum": 50,
"minimum": 1,
"title": "Limit",
"type": "integer"
}
},
"required": [
"q"
],
"title": "search_catalogArguments"
}Esquema de salida
{
"type": "object",
"additionalProperties": true,
"title": "search_catalogDictOutput"
}🟢find_tracks_by_bpm(bpm, tolerance, limit)
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 features. To also constrain by musical key, combine with find_tracks_by_key.
Esquema de entrada
{
"type": "object",
"properties": {
"bpm": {
"description": "Target tempo in BPM.",
"maximum": 300,
"minimum": 20,
"title": "Bpm",
"type": "number"
},
"tolerance": {
"default": 2,
"description": "Plus/minus BPM window (default 2).",
"maximum": 10,
"minimum": 0.5,
"title": "Tolerance",
"type": "number"
},
"limit": {
"default": 10,
"description": "Max tracks (default 10).",
"maximum": 50,
"minimum": 1,
"title": "Limit",
"type": "integer"
}
},
"required": [
"bpm"
],
"title": "find_tracks_by_bpmArguments"
}Esquema de salida
{
"type": "object",
"additionalProperties": true,
"title": "find_tracks_by_bpmDictOutput"
}🟢find_tracks_by_key(key, limit)
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 discover which keys mix well with a given key first, use find_compatible_keys.
Esquema de entrada
{
"type": "object",
"properties": {
"key": {
"description": "Camelot ('8A'), Open Key ('1m'), or key name ('A-Minor', 'F#-Major').",
"maxLength": 20,
"minLength": 1,
"title": "Key",
"type": "string"
},
"limit": {
"default": 10,
"description": "Max tracks (default 10).",
"maximum": 50,
"minimum": 1,
"title": "Limit",
"type": "integer"
}
},
"required": [
"key"
],
"title": "find_tracks_by_keyArguments"
}Esquema de salida
{
"type": "object",
"additionalProperties": true,
"title": "find_tracks_by_keyDictOutput"
}🟢find_compatible_keys(camelot, extended)
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 and no quota cost. Pair with find_tracks_by_key to then pull actual tracks in each compatible key.
Esquema de entrada
{
"type": "object",
"properties": {
"camelot": {
"description": "Camelot key, e.g. '8A' or '12B'.",
"maxLength": 3,
"minLength": 2,
"title": "Camelot",
"type": "string"
},
"extended": {
"default": false,
"description": "Also return the +7/-7 energy-boost / energy-drop keys.",
"title": "Extended",
"type": "boolean"
}
},
"required": [
"camelot"
],
"title": "find_compatible_keysArguments"
}Esquema de salida
{
"type": "object",
"additionalProperties": true,
"title": "find_compatible_keysDictOutput"
}🟢score_transition(from_track_id, to_track_id)
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 scores (`harmonic`/`tempo`/`energy`), a `detail` block (key_relation, both Camelot keys, both BPMs, bpm_delta, bpm_octave_matched, both energies, energy_delta), and a one-line human `reason` (e.g. "8A->9A adjacent (+1), 126->128 BPM (+2), energy +0.04 — clean uplifting mix"). Both ids are catalog itunes_track_ids — get them from search_catalog or the itunes_track_id field of a get_audio_features result. Costs 1 quota unit.
Esquema de entrada
{
"type": "object",
"properties": {
"from_track_id": {
"description": "The track you're mixing FROM — a catalog itunes_track_id, e.g. 'apple_ad1829eeccb70f9a'.",
"maxLength": 80,
"minLength": 1,
"title": "From Track Id",
"type": "string"
},
"to_track_id": {
"description": "The candidate track you're mixing INTO — a catalog itunes_track_id.",
"maxLength": 80,
"minLength": 1,
"title": "To Track Id",
"type": "string"
}
},
"required": [
"from_track_id",
"to_track_id"
],
"title": "score_transitionArguments"
}Esquema de salida
{
"type": "object",
"additionalProperties": true,
"title": "score_transitionDictOutput"
}🟢suggest_next_track(seed_track_id, n, min_score, exclude_same_artist, bpm_drift, ...)
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 the seed. GENRE-AWARE by default (cross_genre=auto): off-genre picks that only coincidentally share the seed's key/BPM sink to the bottom — use cross_genre=strict for same-genre-family only, or allow for the old harmonic-only ranking. It is the seed's sonic neighbours re-ranked for a clean mix. Returns `seed`, `count`, and a `suggestions` array of {track, score, components, reason}. seed_track_id is a catalog itunes_track_id from search_catalog or a get_audio_features result. Pair with build_setlist to order a whole crate. Costs 3 quota units.
Esquema de entrada
{
"type": "object",
"properties": {
"seed_track_id": {
"description": "The track currently playing — a catalog itunes_track_id.",
"maxLength": 80,
"minLength": 1,
"title": "Seed Track Id",
"type": "string"
},
"n": {
"default": 10,
"description": "How many next-track suggestions to return (default 10).",
"maximum": 50,
"minimum": 1,
"title": "N",
"type": "integer"
},
"min_score": {
"default": 0,
"description": "Drop candidates below this overall transition score (default 0).",
"maximum": 100,
"minimum": 0,
"title": "Min Score",
"type": "integer"
},
"exclude_same_artist": {
"default": false,
"description": "Drop tracks by the seed's artist (default false).",
"title": "Exclude Same Artist",
"type": "boolean"
},
"bpm_drift": {
"default": 12,
"description": "Max BPM difference pre-filter before scoring (default 12).",
"maximum": 30,
"minimum": 0.5,
"title": "Bpm Drift",
"type": "number"
},
"max_key_distance": {
"default": 2,
"description": "Max Camelot-wheel hops pre-filter before scoring (default 2).",
"maximum": 12,
"minimum": 0,
"title": "Max Key Distance",
"type": "integer"
},
"cross_genre": {
"default": "auto",
"description": "Genre handling: 'auto' (default) keeps picks in a mixable genre lane so an off-genre track that only shares key/BPM sinks to the bottom; 'strict' = same genre-family only; 'allow' = genre-blind (harmonic+tempo+energy only).",
"title": "Cross Genre",
"type": "string"
}
},
"required": [
"seed_track_id"
],
"title": "suggest_next_trackArguments"
}Esquema de salida
{
"type": "object",
"additionalProperties": true,
"title": "suggest_next_trackDictOutput"
}🟢build_setlist(track_ids, arc, start_track_id)
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_score` (0-100), the `tracks` in play order, the per-step `transitions` ({from_index, to_index, score, reason}), and `omitted` (ids not found in the catalog). Feed tracks[].itunes_track_id into a Rekordbox/Serato export to drop the set straight into your DJ software. track_ids are catalog itunes_track_ids. Costs 5 quota units.
Esquema de entrada
{
"type": "object",
"properties": {
"track_ids": {
"description": "The crate to order — 2 to 100 catalog itunes_track_ids.",
"items": {
"type": "string"
},
"maxItems": 100,
"minItems": 2,
"title": "Track Ids",
"type": "array"
},
"arc": {
"default": "peak_time",
"description": "Energy arc: 'peak_time' (default), 'warmup', 'cooldown', or 'flat'.",
"title": "Arc",
"type": "string"
},
"start_track_id": {
"anyOf": [
{
"maxLength": 80,
"type": "string"
},
{
"type": "null"
}
],
"default": null,
"description": "Optional fixed opener — must be one of track_ids.",
"title": "Start Track Id"
}
},
"required": [
"track_ids"
],
"title": "build_setlistArguments"
}Esquema de salida
{
"type": "object",
"additionalProperties": true,
"title": "build_setlistDictOutput"
}🟢get_recommendations(seed_tracks, track, artist, limit, exclude_seed_artists, ...)
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't outrank same-genre picks). Returns `seeds` (each {id, found}), `count`, and `tracks` (each {track, score, genre_relation}; each track carries its `genre`). `genre_relation` is "same", "compatible" (different but mixable family), "cross" (unrelated), or "unknown" (either side has no mapped genre), measured against the PRIMARY seed — the first of your seed_tracks we could actually use, so reordering seed_tracks changes it and a skipped seed never becomes the reference. With a SINGLE seed the field is the ranking's own verdict, so it explains the order (same as suggest_next_track). With SEVERAL seeds the ranking considers ALL of them while the label stays relative to your primary seed, so a "cross" label on a multi-seed call does NOT mean the track was pushed down — it may share a family with another of your seeds. `score` is the raw audio-feature cosine similarity in [0,1]; genre affinity influences the ORDER, not the score, so the list is NOT strictly score-descending. Use cross_genre=strict to return same-genre-family tracks ONLY (off-genre dropped server-side), or allow to disable the genre ranking. seed_tracks are catalog itunes_track_ids from search_catalog or the itunes_track_id field of a get_audio_features result. NO id? Pass `track` (+ optional `artist`) instead and we resolve the name to the best catalog match and seed on it — the resolved track is echoed back as `seed_query`; seed_tracks wins if both are given. TUNING: `min`/`max` are HARD filters and `target` is a preference (nearer ranks higher, nothing removed), over acousticness, danceability, duration_ms, energy, loudness, tempo and valence. NOTE: `popularity` (2026-08-27), `liveness`, `speechiness` (2026-09-26) and `instrumentalness` (2026-09-27) are RETIRED as tunables and return a 400 — popularity recorded how a track entered our catalogue, not audience size; the other three are returned as null for catalogue tracks. energy/danceability/valence are on FreqBlog's own scale (not Spotify's) — derive thresholds from our values rather than reusing Spotify-tuned ones. e.g. min={"tempo": 100}, max={"tempo": 130}, target={"energy": 0.8} for energetic 100-130 BPM tracks. When you tune, the response adds a `filters` block saying what applied, how many tracks each bound removed (`dropped_by`) and whether the bounds ran out of catalogue before `limit` (`limit_reached`) — if the list comes back short, read that BEFORE assuming the catalogue is thin. Costs 2 quota units.
Esquema de entrada
{
"type": "object",
"properties": {
"seed_tracks": {
"anyOf": [
{
"items": {
"type": "string"
},
"maxItems": 5,
"type": "array"
},
{
"type": "null"
}
],
"default": null,
"description": "1-5 catalog itunes_track_ids to base recommendations on, e.g. ['apple_ad1829eeccb70f9a'] (blended into a feature-space centroid). Omit and use track(+artist) to seed by name instead.",
"title": "Seed Tracks"
},
"track": {
"anyOf": [
{
"maxLength": 200,
"type": "string"
},
{
"type": "null"
}
],
"default": null,
"description": "Seed by track NAME instead of an id — resolved to the best catalog match (echoed back as seed_query). Pair with artist to disambiguate. Ignored when seed_tracks is given.",
"title": "Track"
},
"artist": {
"anyOf": [
{
"maxLength": 200,
"type": "string"
},
{
"type": "null"
}
],
"default": null,
"description": "Artist name narrowing the track seed (case-insensitive).",
"title": "Artist"
},
"limit": {
"default": 20,
"description": "Number of recommendations to return (default 20).",
"maximum": 100,
"minimum": 1,
"title": "Limit",
"type": "integer"
},
"exclude_seed_artists": {
"default": false,
"description": "Drop tracks by any of the seed artists (default false).",
"title": "Exclude Seed Artists",
"type": "boolean"
},
"cross_genre": {
"default": "auto",
"description": "Genre handling (mirrors suggest_next_track): 'auto' (default) re-ranks by genre affinity so a feature-close cross-genre track can't outrank same-genre picks; 'strict' = same genre-family only (off-genre dropped server-side); 'allow' = genre-blind (pure audio-feature cosine).",
"title": "Cross Genre",
"type": "string"
},
"min": {
"anyOf": [
{
"additionalProperties": {
"type": "number"
},
"type": "object"
},
{
"type": "null"
}
],
"default": null,
"description": "HARD lower bounds, e.g. {'tempo': 100, 'energy': 0.5}. Tracks below the bound — and tracks we hold no analysed value for — are dropped. Attributes: acousticness, danceability, duration_ms, energy, loudness, tempo, valence.",
"title": "Min"
},
"max": {
"anyOf": [
{
"additionalProperties": {
"type": "number"
},
"type": "object"
},
{
"type": "null"
}
],
"default": null,
"description": "HARD upper bounds, e.g. {'tempo': 130}. Same attributes as `min`. Combine the two for a range.",
"title": "Max"
},
"target": {
"anyOf": [
{
"additionalProperties": {
"type": "number"
},
"type": "object"
},
{
"type": "null"
}
],
"default": null,
"description": "PREFERRED values, e.g. {'energy': 0.8}. Tracks nearer the value rank higher; unlike min/max nothing is removed. Same attributes as `min`.",
"title": "Target"
}
},
"title": "get_recommendationsArguments"
}Esquema de salida
{
"type": "object",
"additionalProperties": true,
"title": "get_recommendationsDictOutput"
}🟢get_related_artists(artist, limit)
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 prolific artist can't dominate) plus a same-genre lift and a cross-genre penalty. Returns `artist`, `count`, and `related` (each {artist_name, score, match_count, sample_track_id}). Pass a sample_track_id straight to get_audio_features or suggest_next_track. Costs 2 quota units.
Esquema de entrada
{
"type": "object",
"properties": {
"artist": {
"description": "Seed artist name (as it appears in the catalog; case-insensitive).",
"maxLength": 200,
"minLength": 1,
"title": "Artist",
"type": "string"
},
"limit": {
"default": 20,
"description": "Number of related artists to return (default 20).",
"maximum": 50,
"minimum": 1,
"title": "Limit",
"type": "integer"
}
},
"required": [
"artist"
],
"title": "get_related_artistsArguments"
}Esquema de salida
{
"type": "object",
"additionalProperties": true,
"title": "get_related_artistsDictOutput"
}🟢tag_track(track, artist, isrc, mbid, spotify_id, ...)
Get a compact, HONESTLY-LABELLED tag list for a track — energy / danceability / valence / acousticness, plus a mood tag and a broad genre tag (instrumentalness is currently null, so it is not tagged). It is a tag-shaped projection of the same open-data analysis get_audio_features returns (no audio upload, no extra compute), so it costs the same 1 quota unit, charged only on a served result. The differentiator vs opaque taggers (e.g. Cyanite) is that EVERY tag carries its own `confidence` and `provenance`: - confidence: measured (our Essentia analysis) | derived (MIREX mood from valence+energy) | model-estimated (AcousticBrainz mood SVM probability — research-grade, raw prob in `value`) | catalog-genre (broad catalogue tag, not fine-grained). - provenance: essentia | valence+energy | acousticbrainz | catalog. `value` is the [0,1] score for numeric tags and null for label-only tags (mood category, genre). Provide AT LEAST ONE identifier: `track` (optionally with `artist`), `isrc`, `mbid`, `spotify_id`, or `track_id` (catalog itunes_track_id). If you know several, send them all — they resolve by precedence (`track` > `isrc` > `track_id` > `mbid` > `spotify_id`) and the rest are ignored, so you never have to pick. The broad, reliable coverage is the MEASURED tags from our Essentia analysis over the analysed catalogue (plus on-demand by name); MBID/ISRC additionally reach 7.5M+ AcousticBrainz recordings WHEN you supply that identifier. Returns { track, count, tags:[{tag, category, value, confidence, provenance}], disclaimer }. For the full numeric feature set use get_audio_features; for nearest tracks use a discovery tool.
Esquema de entrada
{
"type": "object",
"properties": {
"track": {
"anyOf": [
{
"type": "string"
},
{
"type": "null"
}
],
"default": null,
"description": "Track title. Use with `artist` when known. Supply AT LEAST ONE of track/isrc/mbid/spotify_id/track_id. Sending several is fine — they resolve by precedence (track > isrc > track_id > mbid > spotify_id).",
"title": "Track"
},
"artist": {
"anyOf": [
{
"type": "string"
},
{
"type": "null"
}
],
"default": null,
"description": "Artist name. Only used with `track`; improves accuracy.",
"title": "Artist"
},
"isrc": {
"anyOf": [
{
"type": "string"
},
{
"type": "null"
}
],
"default": null,
"description": "ISRC, e.g. 'USUM71900001'.",
"title": "Isrc"
},
"mbid": {
"anyOf": [
{
"type": "string"
},
{
"type": "null"
}
],
"default": null,
"description": "MusicBrainz recording ID (UUID). Tags come from AcousticBrainz for that exact recording.",
"title": "Mbid"
},
"spotify_id": {
"anyOf": [
{
"type": "string"
},
{
"type": "null"
}
],
"default": null,
"description": "Spotify track ID, 'spotify:track:...' URI, or open.spotify.com URL. Resolved per request by reading the track's title from Spotify's public embed page and matching it against our catalogue (no Spotify IDs are stored) — a title several artists share is ambiguous and misses rather than guessing; prefer track (+artist) or isrc.",
"title": "Spotify Id"
},
"track_id": {
"anyOf": [
{
"maxLength": 80,
"type": "string"
},
{
"type": "null"
}
],
"default": null,
"description": "Catalog itunes_track_id from a search_catalog or get_audio_features result.",
"title": "Track Id"
}
},
"title": "tag_trackArguments"
}Esquema de salida
{
"type": "object",
"additionalProperties": true,
"title": "tag_trackDictOutput"
}Comunidad
Evidencia