automation

SuggestArr: Auto Content Recommendations

Name: SuggestArr: Auto Content Recommendations
Author: giuseppe99barchetta

Get fresh content with SuggestArr, a tool, automating movie and TV show suggestions based on recently watched

1,268 stars30 forksPythonGuide quality 8/10Updated 8/17/2026100% 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

Open in another AI app

Opens the app with this repo with the prompt ready to go — no copy-paste needed.

Connect the whole catalog (MCP)

claude mcp add --transport http workflowstacks https://workflowstacks.com/api/mcp

Adds a WorkflowStacks connector to Claude Code: search and load any skill here by chatting.

How SuggestArr: Auto Content Recommendations works

Codeflow

Free to inspect

SuggestArr: Auto Content Recommendations is a large Python project (~50k lines across 190 code files, plus 49 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

Large codebase

~50k lines · 190 code files · ~7 h to skim

Setup

One-command install

Installs like a normal app. Reading the code is optional.

Runs on

Docker

No API keys detected

Python 61%Vue 28%CSS 8%JavaScript 3%

Where to start reading

1
README.md
Start here — what it does and how to install it
2
CLAUDE.md
The instructions the AI actually follows
3
api_service/app.py
Where the program starts running

What's in each folder

client/Frontend / UI97 files

docs/Documentation7 files

api_service/Folder179 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

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

Open in another AI app

Opens the app with this repo with the prompt ready to go — no copy-paste needed.

Connect the whole catalog (MCP)

claude mcp add --transport http workflowstacks https://workflowstacks.com/api/mcp

Adds a WorkflowStacks connector to Claude Code: search and load any skill here by chatting.

Quick Actions

Details

Creator

giuseppe99barchetta

Language

Python