Plekt - Explainable watch sync for Plex, Emby, Jellyfin and Trakt
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Plekt syncs watched status, resume progress and watch history across Plex, Emby, Jellyfin and Trakt. Its activity ledger shows what changed, where it went and why. Self-host it with Docker and SQLite.
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Hi Product Hunt. I built Plekt for the point where one media server becomes three and “watched” is no longer a trustworthy fact.
Plekt keeps a private canonical record on your own hardware, then reconciles watched state, resume progress, and repeat plays across Plex, Emby, Jellyfin, and Trakt. The feature I care most about is the Sync Activity ledger: it shows the source, destination, outcome, reason, and retry context for each delivery instead of hiding everything behind one sync status.
The current release is v2.2.0, AGPL-3.0, self-hosted, and available through Docker Compose. It also includes Now Playing, history, stats, metadata, Seerr integration, and backups.
I would love feedback from people with a mixed media stack: what would you need to see before trusting a local tool with your watch history?
The implementation was heavily AI-assisted under my direction. I reviewed the generated changes, tested the integrations and browser flows, and maintain and review the project. AI is not required at runtime.
Replies
Hi Product Hunt. I built Plekt for the point where one media server becomes three and “watched” is no longer a trustworthy fact.
Plekt keeps a private canonical record on your own hardware, then reconciles watched state, resume progress, and repeat plays across Plex, Emby, Jellyfin, and Trakt. The feature I care most about is the Sync Activity ledger: it shows the source, destination, outcome, reason, and retry context for each delivery instead of hiding everything behind one sync status.
The current release is v2.2.0, AGPL-3.0, self-hosted, and available through Docker Compose. It also includes Now Playing, history, stats, metadata, Seerr integration, and backups.
I would love feedback from people with a mixed media stack: what would you need to see before trusting a local tool with your watch history?
The implementation was heavily AI-assisted under my direction. I reviewed the generated changes, tested the integrations and browser flows, and maintain and review the project. AI is not required at runtime.