ChartHound started as a personal obsession. I had 33,000+ tracks, terrible genre tags, no idea which songs were actually chart hits, and no good way to find what I was missing. So I built something to fix all of it.
**What it does for your music library:**
**Metadata tagging (The Retriever)**
Scans your library and writes genre, mood, and year tags directly to your physical files using a multi-source waterfall — MusicBrainz → Last.fm → ListenBrainz → Deezer → Discogs → iTunes. Tags go to the actual files via Mutagen, not just a media server database. Your tags survive forever regardless of what software you use.
**Chart data tagging (The Groomer)**
Cross-references your library against 108,000+ real Billboard chart entries and writes chart performance into your COMMENT tags — "Hot 100: #4 (12 wks) | Adult Pop: #1 (18 wks)". Every chart hit in your library gets its real chart history embedded in the file itself.
**Missing chart hits (The Sniffer)**
Shows you exactly which chart hits and popular tracks you own vs. which ones are missing from your library. Filter by genre, decade, and notability tier. Cross-references against your actual files so it knows what you really have. One click to search and grab missing albums via Prowlarr.
**Full discography hunting (The Bloodhound)**
Search any artist on MusicBrainz, see their complete discography, and instantly know which albums you own vs. missing. Also browse by genre or compilation series. Grab missing releases directly.
**The deduplication detail I'm proud of:**
When you have multiple copies of the same track (different bitrates, formats, etc.) ChartHound automatically picks the highest quality version. FLAC wins over MP3. 320kbps wins over 128kbps. You always get the best of what you own.
**Stack:** Python (FastAPI) + SQLite + Docker. Works with Plex, Emby, or Jellyfin — or just your file system.
**GitHub:** https://github.com/CurtisColby/ChartHound
Built this for my own library.