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PocketClawvol. 1 · 2026

Hermes Agent on a Raspberry Pi 5

End-to-end install of Hermes Agent on a fresh Raspberry Pi 5 (8 GB), accessed via Tailscale, with Claude as primary LLM.

Prerequisites

  • Raspberry Pi 5 (8 GB) with the official 27W USB-C power supply
  • microSD card (64 GB Class 10 minimum) — or NVMe via the official M.2 HAT (recommended for sustained operation)
  • An Anthropic API key
  • A Tailscale account (free tier is fine)
  • A laptop on the same network for the initial flash

Steps

  1. Flash Raspberry Pi OS Bookworm

    Use Raspberry Pi Imager. Pick Raspberry Pi OS (64-bit) Bookworm. In the customisation menu set hostname, enable SSH with public-key auth, set your wifi credentials. Eject, insert into the Pi, power on, wait for it to come up.

    # On your laptop, after the Pi boots:
    ssh pi@<pi-hostname>.local
    sudo apt update && sudo apt full-upgrade -y
    sudo reboot
  2. Install Tailscale

    Tailscale is the standard way to access the Hermes dashboard without exposing it on a public IP. Free for personal use.

    curl -fsSL https://tailscale.com/install.sh | sh
    sudo tailscale up
    # Follow the auth URL, sign in, approve the device.
  3. Install Docker

    Hermes Agent runs in Docker. Use the convenience script.

    curl -fsSL https://get.docker.com | sh
    sudo usermod -aG docker $USER
    newgrp docker
    docker run hello-world  # verify it works
  4. Pull Hermes Agent

    The official image. Pin to a specific minor version, not latest.

    mkdir -p ~/hermes && cd ~/hermes
    docker pull nousresearch/hermes-agent:2026.4.4
  5. Configure Hermes

    Hermes wants three things: an LLM API key, a sandbox config, and a credential vault. We'll do all three with environment variables for the simplest setup.

    cat > docker-compose.yml <<'EOF'
    services:
      hermes:
        image: nousresearch/hermes-agent:2026.4.4
        container_name: hermes
        restart: unless-stopped
        environment:
          ANTHROPIC_API_KEY: ${ANTHROPIC_API_KEY}
          HERMES_BIND_ADDR: 127.0.0.1:8765
          HERMES_BROWSER_TOOL: "false"  # disable on Pi 5 — too heavy
          HERMES_LOG_PROMPTS: "false"
        volumes:
          - ./data:/data
        ports:
          - "127.0.0.1:8765:8765"
    EOF
    
    # Set your API key (do NOT commit the .env file)
    echo "ANTHROPIC_API_KEY=sk-ant-..." > .env
    chmod 600 .env
  6. Start Hermes

    Launch the container with Docker Compose. Verify it's running.

    docker compose up -d
    docker compose logs -f hermes
    # Ctrl-C to detach. Container keeps running.
  7. Access the dashboard

    Hermes binds to localhost on the Pi, but you'll access it from your laptop via Tailscale. The Pi's Tailscale IP is shown by `tailscale ip`. Open that IP on port 8765 from your laptop.

    tailscale ip -4
    # Returns 100.x.y.z
    
    # On your laptop, open http://100.x.y.z:8765 in a browser.
    # (You can also configure Tailscale Funnel if you want
    #  HTTPS without certificates, see Tailscale docs.)
  8. First conversation

    The dashboard should now show the Hermes UI. Ask it something simple. Verify the response and check the audit log shows the call. If it works, you're done.

Troubleshooting

docker: command not found after install script
Log out and back in (or run `newgrp docker`). The convenience script adds your user to the docker group but the current shell doesn't pick it up until session restart.
Hermes container exits immediately
Check `docker compose logs hermes`. Most common: missing or invalid ANTHROPIC_API_KEY in .env. Less common: port 8765 already in use.
Dashboard slow / hangs
On a Pi 5 (8 GB) with browser tool enabled, the Chromium container will saturate RAM. Confirm HERMES_BROWSER_TOOL=false in the compose file. If it is, check `docker stats` for memory pressure on other containers.
Tailscale unreachable from laptop
Ensure your laptop is also signed into Tailscale and the device is approved in the Tailscale admin console. ACLs default-allow within a tailnet but corporate Tailscale tenants may have restrictive ACLs.

Where to go from here

Add a local LLM fallback with Ollama + Mistral 7B Q4 — useful when Claude is rate-limited and for cost-sensitive subtasks. Or upgrade hardware to a generic Intel mini PC for browser automation support.

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