I built a desktop music discovery app that uses MusicBrainz as its data backbone, and wanted to share it with this community.
BlackTape indexes artists from MusicBrainz and scores them by how unique they are within their genre — using genre tags, scene data, and regional metadata. The more niche an artist is, the higher they surface. It’s
the inverse of how streaming recommendation engines work.
The reason I built on MusicBrainz: 2.6 million artists with structured, community-maintained metadata is a discovery resource that most apps ignore in favor of proprietary APIs. Genre tags, area data, artist
relationships, recording credits — none of this exists in a usable form anywhere else.
What it does:
- Genre/scene search with atomic tag combinations from MusicBrainz
- Discovery feed ranked by uniqueness score
- Full artist pages: discography, tags, related artists, scene context
- Time Machine: browse artists by decade
- Style Map: visual genre navigation
- Natural language search (“find me something like Boards of Canada but from Japan”)
Desktop app (Tauri + SvelteKit), free, open source, no tracking.
GitHub: GitHub - AllTheMachines/BlackTape
Site: https://blacktape.org
Would love feedback from this community — you know the data better than anyone. Especially interested in whether the genre tag usage makes sense and what metadata I’m underutilizing.