Every book has a rhythm. Some chapters read like a slow ballad, others hit like a drum solo — but readers rarely have a way to hear that.

At the same time, readers who finish a chapter and want to talk about it, share a mood, or connect it to a song they were listening to have nowhere natural to do that. Music communities and book communities exist separately, but the emotional overlap between the two has no home.

Songstery exists to close that gap. We're building a platform where readers can attach music to the exact moments in a book that moved them — a chapter, a scene, a feeling — and discover how other readers experienced the same pages through sound. It's part music discovery, part book community, and part shared emotional archive.

Our goal isn't just to recommend songs. It's to give reading a soundtrack that readers build together.

• Book-to-music matching — find or contribute music recommendations tied to specific chapters, not just entire books.
• Spoiler-safe browsing — explore chapters and their associated music without exposing the text itself.
• Community-curated playlists — playlists built around books, authors, and moods, shaped by the community.
• Verified authors — a path for authors to claim their work and engage directly with readers' interpretations.
• Cross-source search — books sourced via Open Library, music sourced via Spotify, unified in one search experience.

Backend runs on Django 5.2.8 with Django REST Framework, JWT authentication, Redis caching, and integrations with the Spotify Web API and Open Library API. The frontend is built with Next.js.

Full architecture, setup instructions, and API reference live in the main repository.

→ View the Songstery repository

We're early, and building in the open. If you're interested in contributing, have feedback, or just want to see where this goes — check out our repositories or reach out through the team.