About MusicWander

MusicWander is an intelligent music discovery radio that helps you escape algorithmic playlists and surface hidden gems from your Last.fm listening history.

The Problem We Solve

Mainstream music platforms favor popular tracks and major-label artists. If you're into niche genres, experimental music, or underground scenes, algorithmic playlists often miss the mark.

MusicWander analyzes your actual listening patterns on Last.fm to find artists and tracks you'll actually like, not what's trending globally.

How MusicWander Works

1. Connect Your Last.fm — We fetch your top artists and tags from the past 3-12 months.
2. Smart Discovery Engine — Our ML algorithm finds similar artists, matches genre tags, and explores tracks liked by users with similar taste.
3. Personalized Radio — Get a curated queue of 30-second previews. Like, dislike, or skip tracks to refine future recommendations.
4. Export Your Finds — Save your liked tracks as JSON or export via Soundiiz.

What You Get (In Practice)

• A balanced discovery engine that leans niche without blocking familiar picks.
• Quick 30-second previews to decide fast.
• Liked-track history stored locally so you can revisit discoveries.
• Export-ready lists for building playlists elsewhere.

Why 30-Second Previews?

MusicWander is not a streaming service. We use iTunes previews to help you discover new music quickly, then you can listen on your preferred platform (Spotify, Apple Music, Bandcamp, etc.).

Limitations (Transparent on Purpose)

• Results depend on your Last.fm history; new accounts may see less accurate matches.
• Some niche or regional artists may have limited preview availability.
• MusicWander is a discovery tool, not a full streaming player.

Privacy-first

MusicWander is built with privacy in mind:

• No user accounts or sign-ups
• All data stored locally in your browser
• No tracking pixels or ads
• Minimal analytics (GoatCounter, privacy-respecting)

Technology Stack

MusicWander is built with vanilla JavaScript, uses the Last.fm API for music data, and iTunes Search API for audio previews. The discovery algorithm combines collaborative filtering, tag co-occurrence, and similarity scoring.

We intentionally keep the stack lightweight so the app loads fast and runs entirely in the browser.

Created By

MusicWander is an independent project by Guillaume Marical, a developer passionate about music discovery and algorithmic transparency.

Not Affiliated

MusicWander is not affiliated with Last.fm, Apple Music, iTunes, or Spotify. All trademarks belong to their respective owners.