automation

SuggestArr: Auto‑populate your media library with fresh picks

Founder‑focused media automation that scans Jellyfin, Plex or Emby watch history and sends tailored movie, TV and anime recommendations to Jellyseer/Overseer. 1.3k+ GitHub stars.

From the repo · “Effortlessly request recommended movies, TV shows and anime to Jellyseer/Overseer based on your recently watched content on Jellyfin, Plex or Emby—let SuggestArr handle it all automatically, keeping your library fresh with new and exciting content!”

1,344 stars+3★ this week46 forksPythonGuide quality 8/10 · reviewed Oct 13Updated 10/20/2026100% free · open source
What it does

SuggestArr automates movie and TV show suggestions based on recently watched content, integrating with Jellyfin, Plex, or Emby to keep your library fresh.

When to use it
  • •You want to discover new content similar to what you've recently watched without manual searching.
  • •Your media library is integrated with Jellyfin, Plex, or Emby and you're looking for automated recommendations.
  • •You need to keep your media collection updated with new and exciting content regularly.
Ready-to-paste prompt
python suggestarr.py --config config.yml --jellyfin-url https://your-jellyfin-server.com
Heads up: Ensure you have Python 3.8 or higher installed, as SuggestArr requires it to function correctly, and also set up your Jellyfin, Plex, or Emby API keys in the config.yml file.
Saves to your device
Use with Claude
New

Skip the builder — one click puts this in Claude, Cursor, Antigravity and more.

🔑 Needs an API key

Works after you add credentials — the setup agent will ask you for them.

Try it instantly — no install
Claude Code
mkdir -p ~/.claude/skills/suggestarr && curl -fsSL https://workflowstacks.com/api/skills/suggestarr/claude-skill -o ~/.claude/skills/suggestarr/SKILL.md
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Connect the whole catalog (MCP)
claude mcp add --transport http workflowstacks https://workflowstacks.com/api/mcp

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How SuggestArr: Auto‑populate your media library with fresh picks works
Codeflow
Free to inspect

SuggestArr: Auto‑populate your media library with fresh picks is a very large Python project (~66k lines across 322 code files, plus 100 test files). Setup is light: installs like a normal app. Reading the code is optional. Last commit this month, MIT license, has a test suite.

Size
Very large codebase
~66k lines · 322 code files · days to read — use, don't read
Setup
One-command install
Installs like a normal app. Reading the code is optional.
Runs on
Docker
No API keys detected
Python 66%Vue 22%JavaScript 11%CSS 1%
Where to start reading
  1. 1
    README.md
    Start here — what it does and how to install it
  2. 2
    CLAUDE.md
    The instructions the AI actually follows
  3. 3
    api_service/app.py
    Where the program starts running
What's in each folder
client/Frontend / UI192 files
docs/Documentation13 files
api_service/Folder258 files
docker/Deployment / infrastructure3 files
unraid/Folder3 files
config/Configuration1 files
.github/CI / automation (GitHub Actions)8 files
READMEHas testsDocumentedCI checksDocker readyMIT licenseUpdated this month
Quick Actions
Details
Creator
giuseppe99barchetta
Language
Python
Category
automation
Published
10/14/2024

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Featured on WorkflowStacks
[![Featured on WorkflowStacks](https://workflowstacks.com/api/badge/suggestarr.svg)](https://workflowstacks.com/skills/suggestarr?utm_source=github&utm_medium=badge)
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