SuggestArr

SuggestArr is an open-source media automation platform with over 1,100 GitHub stars that closes the gap between what you watch and what gets added to your self-hosted media library. It connects to your Jellyfin, Plex, or Emby media server, analyses recent watch history for each user, and uses The Movie Database (TMDb) API to find similar titles — then automatically submits those titles as download requests to your Seer instance. The entire recommendation-to-request cycle runs unattended on a configurable cron schedule, turning a daily manual workflow into a fully automated background service.

Common Use Cases

Home lab operators with a Jellyfin or Plex library use SuggestArr to keep their collection growing automatically based on actual viewing patterns, without manually browsing Seer every day looking for something similar to watch next. Families with shared Plex servers point SuggestArr at specific user accounts so each household member gets recommendations based on their own watch history rather than the shared library average. Power users enable the AI mode to connect SuggestArr to a local Ollama instance, getting personalized recommendations with explanations and the ability to search with natural language queries instead of keyword matching. Users who have accumulated a large backlog use the content filters to exclude genres, low-rated titles, recent releases, or content already available on their streaming subscriptions — keeping the request queue focused on genuinely novel additions.

Key Features

• Watch history ingestion from Jellyfin, Plex, and Emby with per-user targeting
• TMDb-powered similarity matching for movies and TV shows with configurable result limits
• Automated request submission to Seer (formerly Overseerr/Jellyseerr) on a cron schedule
• Content filters: exclude by genre, rating, release year, language, and streaming service availability
• Optional AI recommendation engine using OpenAI, Ollama, Gemini, LiteLLM, or OpenRouter
• Natural language media search powered by LLM integration (beta)
• Web dashboard with real-time filtered log viewer for monitoring automation runs
• First-visit setup wizard: all API keys and service connections configured in the UI after deployment
• SQLite by default with optional PostgreSQL or MySQL for larger multi-user deployments
• Kubernetes-ready health endpoints: liveness probe at /api/health/live and readiness probe at /api/health/ready

Why deploy SuggestArr on Hostinger VPS

SuggestArr is designed to run as a persistent, always-on background service — it needs to be online at scheduled intervals to pull watch history and submit requests, which makes it unsuitable for running on a desktop or laptop that gets shut down regularly. A Hostinger VPS provides the always-on availability the automation requires, with enough resources to handle the periodic TMDb and LLM API calls without impacting other self-hosted services. All recommendation logic and watch history data stays on your own infrastructure rather than being processed by a hosted service. Because SuggestArr uses SQLite by default, the entire deployment is a single container with one named volume — straightforward to back up and lightweight enough to run alongside your existing Jellyfin, Plex, or Seer stack without dedicated resource allocation. Pairing SuggestArr with a co-hosted Seer instance on the same VPS eliminates inter-service latency and keeps all recommendation traffic local.