{"repo":"JSONbored/mem0-aio","free":true,"listed":false,"github":"https://github.com/JSONbored/mem0-aio","clone":"git clone https://github.com/JSONbored/mem0-aio.git","description":"Unraid CA template and Docker build for Mem0 (OpenMemory). This mega-container utilizes s6-overlay to seamlessly bundle the pre-compiled Qdrant Vector Database, the Python FastAPI/MCP server, and the Next.js Dashboard UI into a single, click-and-play local AI memory layer. Built for homelabs, privacy, and true agentic AI memory retention.","language":"Python","stars":20,"topics":["ai","container","docker","fastapi","homelab","llm","long-term-memory","mcp","mem0","mem0-memory"],"license":null,"category":"deployment-docker-iac","readme_excerpt":"mem0-aio An Unraid-first, single-container deployment of Mem0 OpenMemory for people who want the easiest reliable self-hosted install without manually wiring a separate vector database on day one. mem0-aio keeps the critical first-boot dependency bundled: Qdrant plus persistent local storage. The wrapper is opinionated for a predictable beginner install, but it does not hide the real tradeoffs: OpenMemory still needs a valid model/provider configuration to do useful work, external vector backends and hosted model endpoints still need operator knowledge, and exposing the direct MCP/API port is a deliberate security decision rather than a default requirement. What This Image Includes - OpenMemory web UI on port 3000 - OpenMemory API / MCP server on internal localhost port 8765 - Embedded Qdrant vector store - Persistent appdata storage for SQLite and Qdrant state - Upstream backup/export helper scripts bundled into the image - Same-origin UI routing to the API so a standard Unraid install does not need separate browser-facing API networking - Unraid CA template at mem0-aio.xml Beginner Install If you want the simplest supported path: 1. Install the Unraid template. 2. Leave the default appdata path in place. 3. Either set OPENAI API KEY for the hosted quick-start, or set OLLAMA BASE URL to your external native Ollama root URL for the normal local-LLM path. 4. If you use Ollama, also set LLM MODEL and EMBEDDER MODEL to models you already have pulled on that server. 5. Start the ","default_branch":null,"files":null,"tree":[],"storefront":"/r/JSONbored","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/JSONbored/mem0-aio/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}