MCP-Server

FreqBlog Music Metadata

            com.freqblog/music-metadata
        

Daten & Analytik Medien & Inhalte Öffentlich und erreichbar MCP 2026-07-28

Was dieses MCP kann

Analyzes music audio features and supports catalog search, recommendations, harmonic and tempo matching, DJ transition scoring, and setlist generation.

build_setlist

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_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.

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Eingabeschema

{'type': 'object', 'title': 'build_setlistArguments', 'required': ['track_ids'], 'properties': {'arc': {'type': 'string', 'title': 'Arc', 'default': 'peak_time', 'description': "Energy arc: 'peak_time' (default), 'warmup', 'cooldown', or 'flat'."}, 'track_ids': {'type': 'array', 'items': {'type': 'string'}, 'title': 'Track Ids', 'maxItems': 100, 'minItems': 2, 'description': 'The crate to order — 2 to 100 catalog itunes_track_ids.'}, 'start_track_id': {'anyOf': [{'type': 'string', 'maxLength': 80}, {'type': 'null'}], 'title': 'Start Track Id', 'default': None, 'description': 'Optional fixed opener — must be one of track_ids.'}}}

Ausgabeschema

{'type': 'object', 'title': 'build_setlistDictOutput', 'additionalProperties': True}

find_compatible_keys

Find Harmonically 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 and no quota cost. Pair with find_tracks_by_key to then pull actual tracks in each compatible key.

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Eingabeschema

{'type': 'object', 'title': 'find_compatible_keysArguments', 'required': ['camelot'], 'properties': {'camelot': {'type': 'string', 'title': 'Camelot', 'maxLength': 3, 'minLength': 2, 'description': "Camelot key, e.g. '8A' or '12B'."}, 'extended': {'type': 'boolean', 'title': 'Extended', 'default': False, 'description': 'Also return the +7/-7 energy-boost / energy-drop keys.'}}}

Ausgabeschema

{'type': 'object', 'title': 'find_compatible_keysDictOutput', 'additionalProperties': True}

find_tracks_by_bpm

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 features. To also constrain by musical key, combine with find_tracks_by_key.

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Eingabeschema

{'type': 'object', 'title': 'find_tracks_by_bpmArguments', 'required': ['bpm'], 'properties': {'bpm': {'type': 'number', 'title': 'Bpm', 'maximum': 300, 'minimum': 20, 'description': 'Target tempo in BPM.'}, 'limit': {'type': 'integer', 'title': 'Limit', 'default': 10, 'maximum': 50, 'minimum': 1, 'description': 'Max tracks (default 10).'}, 'tolerance': {'type': 'number', 'title': 'Tolerance', 'default': 2.0, 'maximum': 10, 'minimum': 0.5, 'description': 'Plus/minus BPM window (default 2).'}}}

Ausgabeschema

{'type': 'object', 'title': 'find_tracks_by_bpmDictOutput', 'additionalProperties': True}

find_tracks_by_key

Find Tracks by Musical 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 discover which keys mix well with a given key first, use find_compatible_keys.

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Eingabeschema

{'type': 'object', 'title': 'find_tracks_by_keyArguments', 'required': ['key'], 'properties': {'key': {'type': 'string', 'title': 'Key', 'maxLength': 20, 'minLength': 1, 'description': "Camelot ('8A'), Open Key ('1m'), or key name ('A-Minor', 'F#-Major')."}, 'limit': {'type': 'integer', 'title': 'Limit', 'default': 10, 'maximum': 50, 'minimum': 1, 'description': 'Max tracks (default 10).'}}}

Ausgabeschema

{'type': 'object', 'title': 'find_tracks_by_keyDictOutput', 'additionalProperties': True}

get_audio_features

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 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.

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Eingabeschema

{'type': 'object', 'title': 'get_audio_featuresArguments', 'properties': {'isrc': {'anyOf': [{'type': 'string'}, {'type': 'null'}], 'title': 'Isrc', 'default': None, 'description': "ISRC, e.g. 'USUM71900001'."}, 'mbid': {'anyOf': [{'type': 'string'}, {'type': 'null'}], 'title': 'Mbid', 'default': None, 'description': 'MusicBrainz recording ID (UUID). The precise key when there is no ISRC, e.g. pre-1986 recordings.'}, 'track': {'anyOf': [{'type': 'string'}, {'type': 'null'}], 'title': 'Track', 'default': None, '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.'}, 'artist': {'anyOf': [{'type': 'string'}, {'type': 'null'}], 'title': 'Artist', 'default': None, 'description': 'Artist name. Only used with `track`; required when the title is <=2 characters.'}, 'spotify_id': {'anyOf': [{'type': 'string'}, {'type': 'null'}], 'title': 'Spotify Id', 'default': None, '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."}}}

Ausgabeschema

{'type': 'object', 'title': 'get_audio_featuresDictOutput', 'additionalProperties': True}

get_audio_features_batch

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 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.

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Eingabeschema

{'type': 'object', '$defs': {'TrackQuery': {'type': 'object', 'title': 'TrackQuery', 'properties': {'isrc': {'anyOf': [{'type': 'string', 'maxLength': 15}, {'type': 'null'}], 'title': 'Isrc', 'default': None, 'description': "ISRC, e.g. 'USUM71900001' (hyphens optional). Matched exactly first — resolves CJK/K-pop/niche tracks whose fuzzy name-match misses. Supply this OR `track`."}, 'track': {'anyOf': [{'type': 'string', 'maxLength': 200}, {'type': 'null'}], 'title': 'Track', 'default': None, 'description': 'Track title. Supply this OR `isrc` (or both — ISRC is matched exactly first, the name is the fallback).'}, 'artist': {'anyOf': [{'type': 'string', 'maxLength': 200}, {'type': 'null'}], 'title': 'Artist', 'default': None, 'description': 'Artist name (optional, improves name-match accuracy)'}}, 'description': 'One track to look up by name and/or ISRC. Supply `track` or `isrc` (or both); an item\ncarrying neither is skipped by the batch tool (`invalid_no_query`), not an error.'}}, 'title': 'get_audio_features_batchArguments', 'required': ['tracks'], 'properties': {'tracks': {'type': 'array', 'items': {'$ref': '#/$defs/TrackQuery'}, 'title': 'Tracks', 'maxItems': 200, 'minItems': 1, '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`.'}}}

Ausgabeschema

{'type': 'object', 'title': 'get_audio_features_batchDictOutput', 'additionalProperties': True}

get_recommendations

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'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.

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Eingabeschema

{'type': 'object', 'title': 'get_recommendationsArguments', 'properties': {'max': {'anyOf': [{'type': 'object', 'additionalProperties': {'type': 'number'}}, {'type': 'null'}], 'title': 'Max', 'default': None, 'description': "HARD upper bounds, e.g. {'tempo': 130}. Same attributes as `min`. Combine the two for a range."}, 'min': {'anyOf': [{'type': 'object', 'additionalProperties': {'type': 'number'}}, {'type': 'null'}], 'title': 'Min', 'default': None, '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."}, 'limit': {'type': 'integer', 'title': 'Limit', 'default': 20, 'maximum': 100, 'minimum': 1, 'description': 'Number of recommendations to return (default 20).'}, 'track': {'anyOf': [{'type': 'string', 'maxLength': 200}, {'type': 'null'}], 'title': 'Track', 'default': None, '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.'}, 'artist': {'anyOf': [{'type': 'string', 'maxLength': 200}, {'type': 'null'}], 'title': 'Artist', 'default': None, 'description': 'Artist name narrowing the track seed (case-insensitive).'}, 'target': {'anyOf': [{'type': 'object', 'additionalProperties': {'type': 'number'}}, {'type': 'null'}], 'title': 'Target', 'default': None, 'description': "PREFERRED values, e.g. {'energy': 0.8}. Tracks nearer the value rank higher; unlike min/max nothing is removed. Same attributes as `min`."}, 'cross_genre': {'type': 'string', 'title': '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)."}, 'seed_tracks': {'anyOf': [{'type': 'array', 'items': {'type': 'string'}, 'maxItems': 5}, {'type': 'null'}], 'title': 'Seed Tracks', 'default': None, '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."}, 'exclude_seed_artists': {'type': 'boolean', 'title': 'Exclude Seed Artists', 'default': False, 'description': 'Drop tracks by any of the seed artists (default false).'}}}

Ausgabeschema

{'type': 'object', 'title': 'get_recommendationsDictOutput', 'additionalProperties': True}

get_related_artists

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 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.

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Eingabeschema

{'type': 'object', 'title': 'get_related_artistsArguments', 'required': ['artist'], 'properties': {'limit': {'type': 'integer', 'title': 'Limit', 'default': 20, 'maximum': 50, 'minimum': 1, 'description': 'Number of related artists to return (default 20).'}, 'artist': {'type': 'string', 'title': 'Artist', 'maxLength': 200, 'minLength': 1, 'description': 'Seed artist name (as it appears in the catalog; case-insensitive).'}}}

Ausgabeschema

{'type': 'object', 'title': 'get_related_artistsDictOutput', 'additionalProperties': True}

score_transition

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 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.

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Eingabeschema

{'type': 'object', 'title': 'score_transitionArguments', 'required': ['from_track_id', 'to_track_id'], 'properties': {'to_track_id': {'type': 'string', 'title': 'To Track Id', 'maxLength': 80, 'minLength': 1, 'description': "The candidate track you're mixing INTO — a catalog itunes_track_id."}, 'from_track_id': {'type': 'string', 'title': 'From Track Id', 'maxLength': 80, 'minLength': 1, 'description': "The track you're mixing FROM — a catalog itunes_track_id, e.g. 'apple_ad1829eeccb70f9a'."}}}

Ausgabeschema

{'type': 'object', 'title': 'score_transitionDictOutput', 'additionalProperties': True}

search_catalog

Search Music 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 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.

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Eingabeschema

{'type': 'object', 'title': 'search_catalogArguments', 'required': ['q'], 'properties': {'q': {'type': 'string', 'title': 'Q', 'maxLength': 200, 'minLength': 1, 'description': 'Search query — any mix of artist / track / album tokens.'}, 'limit': {'type': 'integer', 'title': 'Limit', 'default': 10, 'maximum': 50, 'minimum': 1, 'description': 'Max results (default 10).'}}}

Ausgabeschema

{'type': 'object', 'title': 'search_catalogDictOutput', 'additionalProperties': True}

suggest_next_track

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 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.

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Eingabeschema

{'type': 'object', 'title': 'suggest_next_trackArguments', 'required': ['seed_track_id'], 'properties': {'n': {'type': 'integer', 'title': 'N', 'default': 10, 'maximum': 50, 'minimum': 1, 'description': 'How many next-track suggestions to return (default 10).'}, 'bpm_drift': {'type': 'number', 'title': 'Bpm Drift', 'default': 12.0, 'maximum': 30, 'minimum': 0.5, 'description': 'Max BPM difference pre-filter before scoring (default 12).'}, 'min_score': {'type': 'integer', 'title': 'Min Score', 'default': 0, 'maximum': 100, 'minimum': 0, 'description': 'Drop candidates below this overall transition score (default 0).'}, 'cross_genre': {'type': 'string', 'title': '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)."}, 'seed_track_id': {'type': 'string', 'title': 'Seed Track Id', 'maxLength': 80, 'minLength': 1, 'description': 'The track currently playing — a catalog itunes_track_id.'}, 'max_key_distance': {'type': 'integer', 'title': 'Max Key Distance', 'default': 2, 'maximum': 12, 'minimum': 0, 'description': 'Max Camelot-wheel hops pre-filter before scoring (default 2).'}, 'exclude_same_artist': {'type': 'boolean', 'title': 'Exclude Same Artist', 'default': False, 'description': "Drop tracks by the seed's artist (default false)."}}}

Ausgabeschema

{'type': 'object', 'title': 'suggest_next_trackDictOutput', 'additionalProperties': True}

tag_track

Tag Track

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.

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Eingabeschema

{'type': 'object', 'title': 'tag_trackArguments', 'properties': {'isrc': {'anyOf': [{'type': 'string'}, {'type': 'null'}], 'title': 'Isrc', 'default': None, 'description': "ISRC, e.g. 'USUM71900001'."}, 'mbid': {'anyOf': [{'type': 'string'}, {'type': 'null'}], 'title': 'Mbid', 'default': None, 'description': 'MusicBrainz recording ID (UUID). Tags come from AcousticBrainz for that exact recording.'}, 'track': {'anyOf': [{'type': 'string'}, {'type': 'null'}], 'title': 'Track', 'default': None, '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).'}, 'artist': {'anyOf': [{'type': 'string'}, {'type': 'null'}], 'title': 'Artist', 'default': None, 'description': 'Artist name. Only used with `track`; improves accuracy.'}, 'track_id': {'anyOf': [{'type': 'string', 'maxLength': 80}, {'type': 'null'}], 'title': 'Track Id', 'default': None, 'description': 'Catalog itunes_track_id from a search_catalog or get_audio_features result.'}, 'spotify_id': {'anyOf': [{'type': 'string'}, {'type': 'null'}], 'title': 'Spotify Id', 'default': None, '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."}}}

Ausgabeschema

{'type': 'object', 'title': 'tag_trackDictOutput', 'additionalProperties': True}

Geändert

                            tag_track
                        

1. October 2026 02:53

Geändert

                            get_audio_features
                        

1. October 2026 02:53

Geändert

                            get_recommendations
                        

29. September 2026 03:02

Geändert

                            get_audio_features
                        

29. September 2026 03:02

Geändert

                            get_recommendations
                        

27. September 2026 02:52

Hinzugefügt

                            tag_track
                        

17. September 2026 12:34

Hinzugefügt

                            get_related_artists
                        

17. September 2026 12:34

Hinzugefügt

                            get_recommendations
                        

17. September 2026 12:34

Hinzugefügt

                            build_setlist
                        

17. September 2026 12:34

Hinzugefügt

                            suggest_next_track
                        

17. September 2026 12:34

Hinzugefügt

                            score_transition
                        

17. September 2026 12:34

Hinzugefügt

                            find_compatible_keys
                        

17. September 2026 12:34

Hinzugefügt

                            find_tracks_by_key
                        

17. September 2026 12:34

Hinzugefügt

                            find_tracks_by_bpm
                        

17. September 2026 12:34

Hinzugefügt

                            search_catalog
                        

17. September 2026 12:34

Hinzugefügt

                            get_audio_features_batch
                        

17. September 2026 12:34

Hinzugefügt

                            get_audio_features
                        

17. September 2026 12:34

Serverdetails

Version

1.1.0

Transport

Streamable HTTP

Tools

Latenz

1477 ms

Letzter Scan

1. October 2026 02:53

Erstmals gesehen

13. September 2026 02:11

Endpunkt

https://mcp.freqblog.com/mcp

Letzte Scans

Erfolgreich

1. October 2026 02:53

Erfolgreich

29. September 2026 03:02

Erfolgreich

27. September 2026 02:52

Erfolgreich

25. September 2026 03:02

Erfolgreich

23. September 2026 02:53

Erfolgreich

21. September 2026 02:59

Erfolgreich

19. September 2026 02:51

Erfolgreich

17. September 2026 12:59

Erfolgreich

17. September 2026 12:34

FreqBlog Music Metadata

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