Community Apps

Browse our large and growing catalog of applications to run in your Unraid server. 

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All the applications you love—built and maintained by a community member who understands what you need on Unraid. Love a particular app or plugin? Donate directly to the developer to support their work.

Created by a legend

Andrew (aka Squid) has worked tirelessly to build and enhance the experience of Community Apps for users like you. Listen to his story.

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Moderators ensure that apps listed in the store offer a safe, compatible, and consistent experience. Learn more about our guidelines.

deepstack's Icon

Deepstack is an AI server that empowers every developer in the world to easily build state-of-the-art AI systems both on-premise and in the cloud. The promises of Artificial Intelligence are huge but becoming a machine learning engineer is hard. Build and deploy AI-powered applications with in-built and custom AI APIs, all offline and self-hosted. See and To use with home assistant see: and Old CPUs without AVX: If you are using an older CPU that doesn't support AVX (Warning: This version hasn't been updated in some time): 1. Add :noavx to the end of the Repository: field. 2. Should look like this: deepquestai/deepstack:noavx GPU: If you wish to use a NVIDIA GPU instead of your CPU: 1. Install Unraid Nvidia Plugin (available in the community apps store): 2. Add :gpu to the end of the Repository: field. Should look like this: deepquestai/deepstack:gpu 3. Add --runtime=nvidia to the Extra Parameters: field (to view this field switch to advanced view by clicking the toggle in the top right next to Basic View) . 4. Copy your GPU UUID to Nvidia Visible Devices:. (Can be found in the Nvidia Driver settings page under nVidia Info:). Should look something like this: GPU-1a2b3456-7890-1cd2-ea34-56b7c8de90a1 *I am not the creator or maintainer of this container I am merely providing the Unraid template.

frigate's Icon

A complete and local NVR designed for Home Assistant with AI object detection. Uses OpenCV and Tensorflow to perform realtime object detection locally for IP cameras. You cas use a integrated or dedicated GPU (Intel/AMD/Nvidia) to perform the image decoding of the input streams of your cameras. Optionally (but highly recommended), you can use multiple devices to perform the object detetion, such as a Google Coral Accelerator Nvidia GPU, OpenVINO (Intel GPU) and Intel NCS2 VPU See the documentation for more details about your specific hardware and needs ( This is a general templeate that aims to give a fast deoplyment for every user so check all the options carefully and remove all the configurations that you are not going to use.