
LidaTube
Finds and fetches missing Lidarr albums using yt-dlp
360 stars 24 forks last commit first released GPL-3.0
Actively maintained
Last commit 21 Aug 2026.
LidaTube is a lightweight service that searches for and downloads missing albums for a Lidarr-managed music library by leveraging yt-dlp as a backend downloader. It integrates with the Lidarr API to discover missing releases and can optionally import fetched tracks back into Lidarr.
Key Features
- Integrates with the Lidarr API to detect missing albums and trigger downloads
- Uses yt-dlp to fetch audio/video sources and extract preferred codecs
- Configurable scheduling to run syncs at specified hours and a thread limit for concurrent jobs
- Match scoring with a configurable minimum match ratio and fallback-to-top-result option
- Optional cookies support for yt-dlp to access restricted content
- Optionally scans the Lidarr library after downloads and can attempt direct import of items
- Docker-friendly (Docker image and docker-compose example) and environment-variable driven configuration
Use Cases
- Automate filling gaps in a Lidarr music collection by fetching missing albums from online sources
- Run scheduled rescans to keep a local music library synchronized with available online releases
- Use as a bridge between Lidarr and yt-dlp for environments where traditional release sources are incomplete
Limitations and Considerations
- Success depends on available online sources and yt-dlp's ability to find/convert suitable files; some albums may not be found or may have incomplete metadata
- Matching is heuristic and may produce false positives; the minimum match ratio must be tuned for accuracy
- Some content (age-restricted or geo-restricted) may require a cookies file to download correctly
- Not a replacement for canonical release sources; quality and tagging depend on the source material and conversion settings
LidaTube is a pragmatic utility for users who want to extend Lidarr with yt-dlp-based fetching. It is suited for automated, scheduled downloads with configurable matching rules and integration options to streamline reimports into Lidarr.
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