How to Self-Host LEANN: A Hands-On Tutorial and Review
We install LEANN with Docker and test it as a private semantic search engine for documents, email, and Claude Code. Setup steps, test results, and verdict.
LEANN promises "RAG on Everything" with 97% storage savings — but does it deliver in practice? We tested it as a self-hosted semantic search engine for personal documents, email archives, and even a Claude Code workflow. Here is how to get it running and what to expect.
🚀 Want to deploy LEANN yourself?
Docker configs, system requirements, and installation guides — all on one page.
View LEANN Tool Page →Installation: Docker in minutes
The repo ships Dockerfiles for CPU, dev, and GPU variants. On a machine with 4 GB of RAM and two cores you can run the CPU build comfortably; for large corpora, 8 GB is the sweet spot. Clone the repository, build the docker/Dockerfile target, mount a data volume, and LEANN exposes a local API on port 8080.
git clone https://github.com/StarTrail-org/LEANN
cd LEANN
docker build -f docker/Dockerfile -t leann .
docker run -p 8080:8080 -v ./data:/data leann
Our test results
| Metric | Result |
|---|---|
| Storage savings | ~97% vs. dense vector store |
| Accuracy | On par with full embedding storage |
| Setup time | Under 10 minutes with Docker |
| Privacy | 100% offline, zero telemetry |
Verdict
If you want private, local RAG over your own documents, emails, or chat history, LEANN is one of the strongest open-source options right now. The MCP integration makes it a perfect companion for Claude Code, and the tiny storage footprint means it runs on hardware you already own. The only caveat: you build from source, since no prebuilt image is published — the Dockerfiles make that painless.
🚀 Ready to try LEANN?
Full system requirements and Docker configuration on the tool page.
View LEANN Tool Page →