
media-stack
A self-hosted stack for media management and streaming, with AI-powered movie and show recommendations. Includes Sonarr, Radarr, qBitTorrent, Prowlarr, Jellyfin, Jellyseerr, Recommendarr, and VPN support.
Stars: 948

media-stack is a self-hosted media ecosystem that combines media management, streaming, AI-powered recommendations, and VPN. It includes tools like Radarr for movie management, Sonarr for TV show management, Prowlarr for torrent indexing, qBittorrent for downloading media, Jellyseerr for media requests, Jellyfin for media streaming, and Recommendarr for AI-powered recommendations. The stack can be deployed with or without a VPN and offers detailed configuration steps for each tool.
README:
A self-hosted media ecosystem that combines media management, streaming, AI-powered recommendations, and VPN.
This stack includes:
- VPN: For secure and private media downloading
- Radarr: For movie management
- Sonarr: For TV show management
- Prowlarr: A torrent indexer manager for Radarr/Sonarr
- qBittorrent: Torrent client for downloading media
- Jellyseerr: To manage media requests
- Jellyfin: Open-source media streamer
- Recommendarr: For AI-powered movie and show recommendations
- Docker version 28.0.1 or later
- Docker compose version v2.33.1 or later
- Older versions may work, but they have not been tested.
⚠️ Warning for ARMv7 Users:
Jellyseerr v2.0.x introduces breaking changes, dropping support for the ARMv7 container image. However, ARM64 support remains available. You will not be able to run Jellyseerr in ARMv7 CPU.
There are three ways to deploy this stack:
- With a VPN (Recommended)
- Without a VPN
- With Recommendarr (An optional tool for AI-generated movie and show recommendations)
NOTE: If you are installing this stack without a VPN, you must use the
no-vpn
profile.
This requirement prevents accidental or unintentional deployment of media-stack without VPN.Running the
docker compose
command without a profile will not deploy anything.Check the installation steps below.
Before deploying the stack, you must first create a Docker network:
docker network create --subnet 172.20.0.0/16 mynetwork
# Update the CIDR range based on your available IP range
When VPN is enabled, qBittorrent and Prowlarr will run behind the VPN for added privacy.
By default, NordVPN is used in docker-compose.yml
, but you can switch to:
- ExpressVPN
- SurfShark
- ProtonVPN
- Custom OpenVPN
- WireGuard VPN
All providers use the OpenVPN protocol.
➡️ Full list of supported VPN providers: VPN Providers
Refer to your VPN provider's documentation to generate an OpenVPN username and password.
For setup instructions, check:
➡️ Gluetun VPN Setup Guide
By default, VPN is disabled in docker-compose.yml
. To enable it, simply comment/uncomment the required lines in the file.
The docker-compose.yml
file includes clear instructions in the comments to guide you through the process.
Once updated, follow the steps below to deploy the stack with VPN.
VPN_SERVICE_PROVIDER=nordvpn OPENVPN_USER=openvpn-username OPENVPN_PASSWORD=openvpn-password SERVER_COUNTRIES=Switzerland RADARR_STATIC_CONTAINER_IP=radarr-container-static-ip SONARR_STATIC_CONTAINER_IP=sonarr-container-static-ip docker compose --profile vpn up -d
# OPTIONAL: Use Nginx as a reverse proxy
# docker compose -f docker-compose-nginx.yml up -d
A static container IP address is needed when Prowlarr is behind a VPN.
Since Prowlarr can only communicate with Radarr and Sonarr using their container IP addresses,
these must be manually assigned to avoid connection issues when containers restart.
Use the following environment variables to set static IPs:
RADARR_STATIC_CONTAINER_IP
SONARR_STATIC_CONTAINER_IP
🚨 Warning: Deploying without a VPN is highly discouraged as it may expose your IP address when torrenting media.
To proceed without VPN, run the following command:
docker compose --profile no-vpn up -d
# OPTIONAL: Use Nginx as a reverse proxy
# docker compose -f docker-compose-nginx.yml up -d
Recommendarr is a web application that uses AI to generate personalized TV show and movie recommendations based on your:
- Sonarr library
- Radarr library
- Jellyfin watchlist and library
- Trakt watchlist (Optional)
Run the following command based on your setup:
COMPOSE_PROFILES=vpn,recommendarr docker compose up -d # With VPN
# COMPOSE_PROFILES=no-vpn,recommendarr docker compose up -d # Without VPN
- Open qBitTorrent at http://localhost:5080. Default username is
admin
. Temporary password can be collected from container logdocker logs qbittorrent
- Go to Tools --> Options --> WebUI --> Change password
- Run below commands on the server
docker exec -it qbittorrent bash # Get inside qBittorrent container
# Above command will get you inside qBittorrent interactive terminal, Run below command in qbt terminal
mkdir /downloads/movies /downloads/tvshows
chown 1000:1000 /downloads/movies /downloads/tvshows
- Open Radarr at http://localhost:7878
- Settings --> Media Management --> Check mark "Movies deleted from disk are automatically unmonitored in Radarr" under File management section --> Save
- Settings --> Media Management --> Scroll to bottom --> Add Root Folder --> Browse to /downloads/movies --> OK
- Settings --> Download clients --> qBittorrent --> Add Host (qbittorrent) and port (5080) --> Username and password --> Test --> Save Note: If VPN is enabled, then qbittorrent is reachable on vpn's service name. In this case use
vpn
in Host field. - Settings --> General --> Enable advance setting --> Select Authentication and add username and password
- Indexer will get automatically added during configuration of Prowlarr. See 'Configure Prowlarr' section.
Sonarr can also be configured in similar way.
Add a movie (After Prowlarr is configured)
- Movies --> Search for a movie --> Add Root folder (/downloads/movies) --> Quality profile --> Add movie
- All queued movies download can be checked here, Activities --> Queue
- Go to qBittorrent (http://localhost:5080) and see if movie is getting downloaded (After movie is queued. This depends on availability of movie in indexers configured in Prowlarr.)
- Open Jellyfin at http://localhost:8096
- When you access the jellyfin for first time using browser, A guided configuration will guide you to configure jellyfin. Just follow the guide.
- Add media library folder and choose /data/movies/
- Open Jellyfin at http://localhost:5055
- When you access the jellyseerr for first time using browser, A guided configuration will guide you to configure jellyseerr. Just follow the guide and provide the required details about sonarr and Radarr.
- Follow the Overseerr document (Jellyseerr is fork of overseerr) for detailed setup - https://docs.overseerr.dev/
- Open Prowlarr at http://localhost:9696
- Settings --> General --> Authentications --> Select Authentication and add username and password
- Add Indexers, Indexers --> Add Indexer --> Search for indexer --> Choose base URL --> Test and Save
- Add application, Settings --> Apps --> Add application --> Choose Radarr --> Prowlarr server (http://prowlarr:9696) --> Radarr server (http://radarr:7878) --> API Key --> Test and Save
- Add application, Settings --> Apps --> Add application --> Choose Sonarr --> Prowlarr server (http://prowlarr:9696) --> Sonarr server (http://sonarr:8989) --> API Key --> Test and Save
- This will add indexers in respective apps automatically.
Note: If VPN is enabled, then Prowlarr will not be able to reach radarr and sonarr with localhost or container service name. In that case use static IP for sonarr and radarr in radarr/sonarr server field (for e.g. http://172.19.0.5:8989). Prowlar will also be not reachable with its container/service name. Use http://vpn:9696
instead in prowlar server field.
Recommendarr is an AI based movies/tvshows recommendation tool. To use this you will need any OpenAI API URL and API key with atleast one LLM model running. You can host your own OpenAI server with AI model using ollama or LM Studio. Or you can check https://openrouter.ai
for limited-free LLMs.
- Open Recommendarr at http://localhost:3000
- Login with default username
admin
and password1234
- Settings --> Account --> Change Password and change your admin password
- Settings --> AI service --> API URL (Add OpenAI server API URL) --> API Key (Add OpenAPI server API key) --> Fetch available models --> Set Max tokens (best to keep it under 2000) --> Set Temperature (Best to keep at 0.8)
- Settings --> Sonarr --> Sonarr URL (http://sonarr:8989) --> API Keys (Sonarr API Key) --> Test Connection --> Save Sonarr setting
- Settings --> Radarr --> Radarr URL (http://radarr:7878) --> API Keys (Radarr API Key) --> Test Connection --> Save Radarr setting
- Settings --> Jellyfin --> Jellyfin URL (http://jellyfin:8096) --> API Keys (Jellyfin API Key) --> User ID (Add your jellyfin user id) --> Test Connection --> Save Jellyfin settings
- Test recommendarr: Recommendations --> Choose LLM Model from drop down list --> Enable Jellyfin Watch History toggle --> Select language --> Choose genres --> Discover recommendations
- You should be able to see recommendations based on your Jellyfin watch history
- Get inside Nginx container
cd /etc/nginx/conf.d
- Add proxies for all tools.
docker cp nginx.conf nginx:/etc/nginx/conf.d/default.conf && docker exec -it nginx nginx -s reload
- Close ports of other tools in firewall/security groups except port 80 and 443.
- Open port 80 and 443.
- Get inside Nginx container and install certbot and certbot-nginx
apk add certbot certbot-nginx
- Add URL in server block. e.g.
server_name localhost mediastack.example.com;
in /etc/nginx/conf.d/default.conf - Run
certbot --nginx
and provide details asked.
- Settings --> General --> URL Base --> Add base (/radarr)
- Add below proxy in nginx configuration
location /radarr {
proxy_pass http://radarr:7878;
proxy_set_header Host $host;
proxy_set_header X-Real-IP $remote_addr;
proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for;
proxy_http_version 1.1;
proxy_set_header Upgrade $http_upgrade;
proxy_set_header Connection $http_connection;
}
- Restart containers.
- Settings --> General --> URL Base --> Add base (/sonarr)
- Add below proxy in nginx configuration
location /sonarr {
proxy_pass http://sonarr:8989;
proxy_set_header Host $host;
proxy_set_header X-Real-IP $remote_addr;
proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for;
proxy_http_version 1.1;
proxy_set_header Upgrade $http_upgrade;
proxy_set_header Connection $http_connection;
}
- Settings --> General --> URL Base --> Add base (/prowlarr)
- Add below proxy in nginx configuration
This may need to change configurations in indexers and base in URL.
location /prowlarr {
proxy_pass http://prowlarr:9696; # Comment this line if VPN is enabled.
# proxy_pass http://vpn:9696; # Uncomment this line if VPN is enabled.
proxy_set_header Host $host;
proxy_set_header X-Real-IP $remote_addr;
proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for;
proxy_http_version 1.1;
proxy_set_header Upgrade $http_upgrade;
proxy_set_header Connection $http_connection;
}
- Restart containers.
Note: If VPN is enabled, then Prowlarr is reachable on vpn's service name
location /qbt/ {
proxy_pass http://qbittorrent:5080/; # Comment this line if VPN is enabled.
# proxy_pass http://vpn:5080/; # Uncomment this line if VPN is enabled.
proxy_http_version 1.1;
proxy_set_header Host http://qbittorrent:5080; # Comment this line if VPN is enabled.
# proxy_set_header Host http://vpn:5080; # Uncomment this line if VPN is enabled.
proxy_set_header X-Forwarded-Host $http_host;
proxy_set_header X-Forwarded-For $remote_addr;
proxy_cookie_path / "/; Secure";
}
Note: If VPN is enabled, then qbittorrent is reachable on vpn's service name
- Add base URL, Admin Dashboard -> Networking -> Base URL (/jellyfin)
- Add below config in Ngix config
location /jellyfin {
return 302 $scheme://$host/jellyfin/;
}
location /jellyfin/ {
proxy_pass http://jellyfin:8096/jellyfin/;
proxy_pass_request_headers on;
proxy_set_header Host $host;
proxy_set_header X-Real-IP $remote_addr;
proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for;
proxy_set_header X-Forwarded-Proto $scheme;
proxy_set_header X-Forwarded-Host $http_host;
proxy_set_header Upgrade $http_upgrade;
proxy_set_header Connection $http_connection;
# Disable buffering when the nginx proxy gets very resource heavy upon streaming
proxy_buffering off;
}
Currently Jellyseerr/Overseerr doesnot officially support the subfolder/path reverse proxy. They have a workaround documented here without an official support. Find it here
location / {
proxy_pass http://127.0.0.1:5055;
proxy_set_header Referer $http_referer;
proxy_set_header Host $host;
proxy_set_header X-Real-IP $remote_addr;
proxy_set_header X-Real-Port $remote_port;
proxy_set_header X-Forwarded-Host $host:$remote_port;
proxy_set_header X-Forwarded-Server $host;
proxy_set_header X-Forwarded-Port $remote_port;
proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for;
proxy_set_header X-Forwarded-Proto $scheme;
proxy_set_header X-Forwarded-Ssl on;
}
- Restart containers
Neither the author nor the developers of the code in this repository condone or encourage downloading, sharing, seeding, or peering of copyrighted material.
Such activities are illegal under international laws.This project is intended for educational purposes only.
For Tasks:
Click tags to check more tools for each tasksFor Jobs:
Alternative AI tools for media-stack
Similar Open Source Tools

media-stack
media-stack is a self-hosted media ecosystem that combines media management, streaming, AI-powered recommendations, and VPN. It includes tools like Radarr for movie management, Sonarr for TV show management, Prowlarr for torrent indexing, qBittorrent for downloading media, Jellyseerr for media requests, Jellyfin for media streaming, and Recommendarr for AI-powered recommendations. The stack can be deployed with or without a VPN and offers detailed configuration steps for each tool.

ebook2audiobook
ebook2audiobook is a CPU/GPU converter tool that converts eBooks to audiobooks with chapters and metadata using tools like Calibre, ffmpeg, XTTSv2, and Fairseq. It supports voice cloning and a wide range of languages. The tool is designed to run on 4GB RAM and provides a new v2.0 Web GUI interface for user-friendly interaction. Users can convert eBooks to text format, split eBooks into chapters, and utilize high-quality text-to-speech functionalities. Supported languages include Arabic, Chinese, English, French, German, Hindi, and many more. The tool can be used for legal, non-DRM eBooks only and should be used responsibly in compliance with applicable laws.

Visionatrix
Visionatrix is a project aimed at providing easy use of ComfyUI workflows. It offers simplified setup and update processes, a minimalistic UI for daily workflow use, stable workflows with versioning and update support, scalability for multiple instances and task workers, multiple user support with integration of different user backends, LLM power for integration with Ollama/Gemini, and seamless integration as a service with backend endpoints and webhook support. The project is approaching version 1.0 release and welcomes new ideas for further implementation.

probe
Probe is an AI-friendly, fully local, semantic code search tool designed to power the next generation of AI coding assistants. It combines the speed of ripgrep with the code-aware parsing of tree-sitter to deliver precise results with complete code blocks, making it perfect for large codebases and AI-driven development workflows. Probe is fully local, keeping code on the user's machine without relying on external APIs. It supports multiple languages, offers various search options, and can be used in CLI mode, MCP server mode, AI chat mode, and web interface. The tool is designed to be flexible, fast, and accurate, providing developers and AI models with full context and relevant code blocks for efficient code exploration and understanding.

AgC
AgC is an open-core platform designed for deploying, running, and orchestrating AI agents at scale. It treats agents as first-class compute units, providing a modular, observable, cloud-neutral, and production-ready environment. Open Agentic Compute empowers developers and organizations to run agents like cloud-native workloads without lock-in.

vearch
Vearch is a cloud-native distributed vector database designed for efficient similarity search of embedding vectors in AI applications. It supports hybrid search with vector search and scalar filtering, offers fast vector retrieval from millions of objects in milliseconds, and ensures scalability and reliability through replication and elastic scaling out. Users can deploy Vearch cluster on Kubernetes, add charts from the repository or locally, start with Docker-compose, or compile from source code. The tool includes components like Master for schema management, Router for RESTful API, and PartitionServer for hosting document partitions with raft-based replication. Vearch can be used for building visual search systems for indexing images and offers a Python SDK for easy installation and usage. The tool is suitable for AI developers and researchers looking for efficient vector search capabilities in their applications.

probe
Probe is an AI-friendly, fully local, semantic code search tool designed to power the next generation of AI coding assistants. It combines the speed of ripgrep with the code-aware parsing of tree-sitter to deliver precise results with complete code blocks, making it perfect for large codebases and AI-driven development workflows. Probe supports various features like AI-friendly code extraction, fully local operation without external APIs, fast scanning of large codebases, accurate code structure parsing, re-rankers and NLP methods for better search results, multi-language support, interactive AI chat mode, and flexibility to run as a CLI tool, MCP server, or interactive AI chat.

Zero
Zero is an open-source AI email solution that allows users to self-host their email app while integrating external services like Gmail. It aims to modernize and enhance emails through AI agents, offering features like open-source transparency, AI-driven enhancements, data privacy, self-hosting freedom, unified inbox, customizable UI, and developer-friendly extensibility. Built with modern technologies, Zero provides a reliable tech stack including Next.js, React, TypeScript, TailwindCSS, Node.js, Drizzle ORM, and PostgreSQL. Users can set up Zero using standard setup or Dev Container setup for VS Code users, with detailed environment setup instructions for Better Auth, Google OAuth, and optional GitHub OAuth. Database setup involves starting a local PostgreSQL instance, setting up database connection, and executing database commands for dependencies, tables, migrations, and content viewing.

aomail-app
Aomail is an intelligent, open-source email management platform with AI capabilities. It offers email provider integration, AI-powered tools for smart categorization and assistance, analytics and management features. Users can self-host for complete control. Coming soon features include AI custom rules, platform integration with Discord & Slack, and support for various AI providers. The tool is designed to revolutionize email management by providing advanced AI features and analytics.

swift-chat
SwiftChat is a fast and responsive AI chat application developed with React Native and powered by Amazon Bedrock. It offers real-time streaming conversations, AI image generation, multimodal support, conversation history management, and cross-platform compatibility across Android, iOS, and macOS. The app supports multiple AI models like Amazon Bedrock, Ollama, DeepSeek, and OpenAI, and features a customizable system prompt assistant. With a minimalist design philosophy and robust privacy protection, SwiftChat delivers a seamless chat experience with various features like rich Markdown support, comprehensive multimodal analysis, creative image suite, and quick access tools. The app prioritizes speed in launch, request, render, and storage, ensuring a fast and efficient user experience. SwiftChat also emphasizes app privacy and security by encrypting API key storage, minimal permission requirements, local-only data storage, and a privacy-first approach.

zotero-mcp
Zotero MCP is an open-source project that integrates AI capabilities with Zotero using the Model Context Protocol. It consists of a Zotero plugin and an MCP server, enabling AI assistants to search, retrieve, and cite references from Zotero library. The project features a unified architecture with an integrated MCP server, eliminating the need for a separate server process. It provides features like intelligent search, detailed reference information, filtering by tags and identifiers, aiding in academic tasks such as literature reviews and citation management.

CrewAI-Studio
CrewAI Studio is an application with a user-friendly interface for interacting with CrewAI, offering support for multiple platforms and various backend providers. It allows users to run crews in the background, export single-page apps, and use custom tools for APIs and file writing. The roadmap includes features like better import/export, human input, chat functionality, automatic crew creation, and multiuser environment support.

ai-doc-gen
An AI-powered code documentation generator that automatically analyzes repositories and creates comprehensive documentation using advanced language models. The system employs a multi-agent architecture to perform specialized code analysis and generate structured documentation.

meeting-minutes
An open-source AI assistant for taking meeting notes that captures live meeting audio, transcribes it in real-time, and generates summaries while ensuring user privacy. Perfect for teams to focus on discussions while automatically capturing and organizing meeting content without external servers or complex infrastructure. Features include modern UI, real-time audio capture, speaker diarization, local processing for privacy, and more. The tool also offers a Rust-based implementation for better performance and native integration, with features like live transcription, speaker diarization, and a rich text editor for notes. Future plans include database connection for saving meeting minutes, improving summarization quality, and adding download options for meeting transcriptions and summaries. The backend supports multiple LLM providers through a unified interface, with configurations for Anthropic, Groq, and Ollama models. System architecture includes core components like audio capture service, transcription engine, LLM orchestrator, data services, and API layer. Prerequisites for setup include Node.js, Python, FFmpeg, and Rust. Development guidelines emphasize project structure, testing, documentation, type hints, and ESLint configuration. Contributions are welcome under the MIT License.

Pixelle-MCP
Pixelle-MCP is a multi-channel publishing tool designed to streamline the process of publishing content across various social media platforms. It allows users to create, schedule, and publish posts simultaneously on platforms such as Facebook, Twitter, and Instagram. With a user-friendly interface and advanced scheduling features, Pixelle-MCP helps users save time and effort in managing their social media presence. The tool also provides analytics and insights to track the performance of posts and optimize content strategy. Whether you are a social media manager, content creator, or digital marketer, Pixelle-MCP is a valuable tool to enhance your online presence and engage with your audience effectively.

Dungeo_ai
OpenSource AI Tool for interactive text adventure with AI-generated storytelling and optional TTS narration support. Explore, role-play, and create story-driven adventures using AI. Requires Python 3.10+, pip, Ollama, NVIDIA CUDA Toolkit, git, and AllTalk TTS. Includes different modes for varied experiences and commands for gameplay. Licensed under MIT License with credit requirement for commercial use.
For similar tasks

trieve
Trieve is an advanced relevance API for hybrid search, recommendations, and RAG. It offers a range of features including self-hosting, semantic dense vector search, typo tolerant full-text/neural search, sub-sentence highlighting, recommendations, convenient RAG API routes, the ability to bring your own models, hybrid search with cross-encoder re-ranking, recency biasing, tunable popularity-based ranking, filtering, duplicate detection, and grouping. Trieve is designed to be flexible and customizable, allowing users to tailor it to their specific needs. It is also easy to use, with a simple API and well-documented features.

CoLLM
CoLLM is a novel method that integrates collaborative information into Large Language Models (LLMs) for recommendation. It converts recommendation data into language prompts, encodes them with both textual and collaborative information, and uses a two-step tuning method to train the model. The method incorporates user/item ID fields in prompts and employs a conventional collaborative model to generate user/item representations. CoLLM is built upon MiniGPT-4 and utilizes pretrained Vicuna weights for training.

media-stack
media-stack is a self-hosted media ecosystem that combines media management, streaming, AI-powered recommendations, and VPN. It includes tools like Radarr for movie management, Sonarr for TV show management, Prowlarr for torrent indexing, qBittorrent for downloading media, Jellyseerr for media requests, Jellyfin for media streaming, and Recommendarr for AI-powered recommendations. The stack can be deployed with or without a VPN and offers detailed configuration steps for each tool.

Genkit
Genkit is an open-source framework for building full-stack AI-powered applications, used in production by Google's Firebase. It provides SDKs for JavaScript/TypeScript (Stable), Go (Beta), and Python (Alpha) with unified interface for integrating AI models from providers like Google, OpenAI, Anthropic, Ollama. Rapidly build chatbots, automations, and recommendation systems using streamlined APIs for multimodal content, structured outputs, tool calling, and agentic workflows. Genkit simplifies AI integration with open-source SDK, unified APIs, and offers text and image generation, structured data generation, tool calling, prompt templating, persisted chat interfaces, AI workflows, and AI-powered data retrieval (RAG).

Olares
Olares is an open-source sovereign cloud OS designed for local AI, enabling users to build their own AI assistants, sync data across devices, self-host their workspace, stream media, and more within a sovereign cloud environment. Users can effortlessly run leading AI models, deploy open-source AI apps, access AI apps and models anywhere, and benefit from integrated AI for personalized interactions. Olares offers features like edge AI, personal data repository, self-hosted workspace, private media server, smart home hub, and user-owned decentralized social media. The platform provides enterprise-grade security, secure application ecosystem, unified file system and database, single sign-on, AI capabilities, built-in applications, seamless access, and development tools. Olares is compatible with Linux, Raspberry Pi, Mac, and Windows, and offers a wide range of system-level applications, third-party components and services, and additional libraries and components.
For similar jobs

media-stack
media-stack is a self-hosted media ecosystem that combines media management, streaming, AI-powered recommendations, and VPN. It includes tools like Radarr for movie management, Sonarr for TV show management, Prowlarr for torrent indexing, qBittorrent for downloading media, Jellyseerr for media requests, Jellyfin for media streaming, and Recommendarr for AI-powered recommendations. The stack can be deployed with or without a VPN and offers detailed configuration steps for each tool.