
Kavita
Self-hosted digital library server for ebooks, comics, and manga

Kavita is an open-source, cross-platform reading server that organizes and serves ebooks, comics, manga and image-based books. It provides responsive built-in readers, metadata management and developer APIs to integrate with third-party tools and OPDS-compatible apps.
Key Features
- Built-in readers optimized per format (EPUB, PDF, CBZ/CBR, raw images) with single/double-page and webtoon modes
- Rich metadata support and parsing (filename heuristics, ComicInfo.xml) with filtering, search and smart collections
- OPDS feeds and a documented REST API/OpenAPI for external integrations and mobile apps
- User and role management with OIDC support and granular access/age restrictions
- Annotations/highlights for EPUB with export capabilities and shareable reading lists
- Folder-watching automatic import, full-text/index-backed search, ratings, reviews and reading progress tracking
- Official Docker support and cross-platform distribution; optional Kavita+ subscription adds metadata sync, external ratings/reviews and progress sync
Use Cases
- Host and share a personal or household digital book/comics library with device-optimized readers
- Integrate a catalog into third-party OPDS-compatible reader apps or custom frontends via the REST API
- Catalog and manage large collections with rich metadata, curated reading lists and shared user permissions
Limitations and Considerations
- Kavita uses a file-based SQLite backend by design; it does not provide official support for external RDBMS backends, which can limit scalability and introduce locking concerns at very large library sizes
- Some advanced features (external metadata sync, aggregated ratings/reviews, progress sync) require the optional paid Kavita+ service, which is node-locked to a server
Kavita is focused on delivering a full-featured self-hosted reading experience with extensible APIs and active community development. It is suitable for home and small-group deployments that need device-optimized readers, rich metadata and OPDS integrations.
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