Building an OpenClaw Multi-Agent Assistant on Raspberry Pi 5

A developer on r/openclaw is building JDM Assistant — a multi-agent personal assistant on a Raspberry Pi 5, using OpenClaw as the central platform and orchestration layer. The architecture takes inspiration from a hospital: a primary agent acts as the 'director', receiving requests via Telegram or cron jobs, routing them to specialized agents for health, calendar, smart home, shopping, documents, and finance.

OpenClaw's role

In this design, OpenClaw manages:

• Agent workspaces and internal communication
• Task routing between the main agent and specialized agents
• Connections to external AI providers (and later local LLMs)
• Approved tools, Python scripts, and application integrations
• Knowledge, documents, memories, and workflow state
• Permissions, confirmations, logging, and security rules

The plan includes a standby OpenClaw instance that can take over if the primary service fails, and an independent watchdog (outside the main stack) that monitors the system and alerts via email.

Security-first design

Security is a core concern. Agents should not directly access external AI services, scripts, email, calendar, or smart-home devices. All actions go through controlled OpenClaw tools and security gates. Sensitive operations — sending emails, modifying appointments, controlling devices, placing orders — require explicit approval unless the user has pre-authorized a specific automation.

Deployment and roadmap

The entire OpenClaw environment runs as an isolated Docker stack. The initial scope includes Telegram integration, the main agent, strict permissions, and a few simple specialized agents. Future plans: local LLMs, a tested Python tool library, reusable workflows, a knowledge archive, and modular 'departments' or units.

The post notes that two workspaces with separate agents are already running successfully, demonstrating the approach's feasibility.

What's missing?

For a production-grade assistant, consider adding: health checks for each agent, circuit breakers between agents and external APIs, audit trails, and rate limiting. Also, a backup strategy for the knowledge store and state. The watchdog could use systemd or a sidecar container, and the standby instance should be tested with a failover script.

While the post focuses on the architecture, it doesn't yet include concrete OpenClaw configuration snippets. Refer to the Reddit thread for the poster's ongoing progress and community advice.