Docker homelab AI assistant with PicoClaw

Run PicoClaw as a Dockerized AI assistant in your homelab so you can manage cron jobs, webhooks, and automations from a single self‑hosted container.

Many homelab setups already use Docker or docker‑compose on a NAS, mini‑PC, or small server. PicoClaw fits nicely into this stack: it's light on CPU and memory, easy to deploy as a container, and can talk to your LLM providers or local models.

1. Requirements

  • A Linux server, homelab node, or NAS with Docker installed
  • Network access to your chosen LLM provider or local model endpoint
  • A configuration file for PicoClaw with providers and workflows

2. Run PicoClaw with Docker

The basic pattern is to mount your configuration into the container and expose any ports you need for webhooks or dashboards.

Example docker run

docker run -d --name picoclaw \
  -v $PWD/config.yaml:/etc/picoclaw/config.yaml \
  -p 8080:8080 \
  ghcr.io/sipeed/picoclaw:latest

See the Docker page for more container configuration options and environment variables.

3. Add PicoClaw to docker-compose

If you manage your homelab with docker‑compose, add a picoclaw service alongside your databases, dashboards, and other apps. Give it volumes for configuration and logs, and optional dependencies on databases or queues if your workflows use them.

4. Homelab AI use cases

  • Scheduled reports – use cron‑style scheduling to summarise metrics, backup logs, or uptime checks.
  • Webhook automations – let external tools send events to PicoClaw, which calls an LLM and routes the result to chat or email.
  • On‑prem AI helpers – keep prompts and data inside your lab while still leveraging powerful models.

For more background on self‑hosting PicoClaw beyond Docker, see the self‑hosted AI assistant guide.