navidrome-mcp

An MCP server for Navidrome that builds playlists which actually match a described mood — grounded in what you own, what you have listened to, and how you yourself have labelled your music.

Why this exists

Navidrome's API alone cannot do this, for three concrete reasons:

1. Its REST filtering is exact-match only. year=1997 works; year=1990-1999 silently returns nothing. There are no ranges and no AND/OR, so a query like "90s rock I haven't played in a year, max 2 per artist" is not expressible.

2. It keeps no listen history. Only a playCount and a last playDate. There is no way to ask "what do I put on at 7am on a Tuesday".

3. Nothing in the library says how a track feels. Measured on a real 9,311-track library: 32 genres with Rock alone covering 47%, BPM present on 24 tracks (0.3%), ReplayGain on 222 (2%), MusicBrainz recording IDs on 222 (2%). That last number also rules out AcousticBrainz as a primary mood source — its audio-derived mood models are keyed by MBID, and resolving the rest via ISRC → MusicBrainz (rate-limited to 1 req/s) would still only reach ~23% of the library.

So this server maintains its own index and joins three sources:

It also treats your existing curated playlists as your mood vocabulary. If you have playlists called golden hour, cranked and slow shreds, those words already mean something specific in your library — far more than a generic genre ever will.

Related MCP server: Navidrome-MCP

The mood pass

Those playlists cover maybe 40% of a library, so on their own they can only answer mood questions about tracks you already filed. A one-time enrichment pass closes that gap: every track gets energy, valence, intensity, acoustic-vs-electronic, free-form descriptors, the curated vibe it reads as, and the times of day it fits.

The inference is grounded in your own playlists — they're a hand-labelled training set in your own words — so unfiled tracks land in the same space as the ones you filed. Results are cached permanently, so this runs once and afterwards only picks up new music.

Cost stays small through three things: batching ~40 tracks per request, prompt-caching the large identical taxonomy prefix (the first batch runs alone, so the rest hit a warm cache instead of all missing it concurrently), and running with thinking disabled — this is classification, not reasoning. Set ANTHROPIC_API_KEY to enable it and MOOD_MODEL to trade quality for spend; without a key everything else still works and only the mood filters go dark.

Design notes

• In-memory index, no database. A full library pull is ~20s for ~10k tracks; once local, every compound query is a single array pass. A JSON snapshot on disk makes restarts instant. Deliberately no native dependency, so it installs under npm ci --ignore-scripts on Node 20.

• The index is a cache, never a source of truth. If the snapshot is missing or unreadable the server just re-syncs.

• Navidrome's own compound engine is still exposed via create_smart_playlist, for standing playlists that should keep re-evaluating server-side. Note those rules can only see Navidrome's own fields — not ListenBrainz listens or Last.fm tags.

Tools

Prompt: daylist — generates a Spotify-style daylist for the current hour.

Configuration

Licence

MIT