Best Raspberry Pi Projects for OpenClaw AI Agents

OpenClaw is an open-source AI agent framework that gives an LLM the ability to take action: run commands, call APIs, manage files, and interact with services on your behalf. It supports channels like Telegram, Discord, WhatsApp, Slack, and Signal out of the box.

The Raspberry Pi 5 with 8GB RAM has become the go-to hardware for running OpenClaw as a dedicated, always-on agent. The Pi itself doesn't run the LLM locally. Instead, it acts as a lightweight controller that coordinates workflows while remote LLM APIs (OpenAI, Anthropic, Google) handle the heavy computation. This keeps power draw around 5W, or roughly published pricing in electricity.

Recommended hardware:

• Raspberry Pi 5 with 8GB RAM (Pi 4 8GB also works)
• USB SSD or NVMe drive (more reliable than SD cards for 24/7 operation)
• Stable internet connection
• Total cost: under $100

The setup process is straightforward. Flash Raspberry Pi OS Lite, install Node.js 22+, run the OpenClaw installer, and complete the onboarding wizard. The Sunfounder setup guide walks through each step, including creating a systemd service so the agent starts automatically on boot.

This is the most popular OpenClaw Pi project, and for good reason. Connecting OpenClaw to Home Assistant turns your smart home from a collection of apps into something you can talk to naturally.

OpenClaw has a dedicated Home Assistant Add-On that runs in a supervised container with direct access to your HA configuration. Once connected via Home Assistant's REST API, you can control devices with plain language:

• "Turn off all the lights downstairs"
• "Set the bedroom to 21 degrees"
• "When I leave home, turn off the lights and lock the front door"

That last example is where it gets interesting. OpenClaw doesn't just toggle switches. It can create automations on the fly, manage scenes, and read entity states to make decisions. A Pi 5 with 8GB handles Home Assistant and OpenClaw together for a small to medium smart home with roughly 50 to 100 devices.

What you need: Raspberry Pi 5, Home Assistant OS (or a separate HA instance), a long-lived access token from your HA profile, and the ha-mcp skill installed in OpenClaw.

Best for: Anyone already running Home Assistant who wants conversational control without cloud dependencies.

OpenClaw supports over 20 messaging channels natively: Telegram, Discord, Slack, WhatsApp, Signal, iMessage, Matrix, Microsoft Teams, and more. Running it on a Pi gives you a personal AI assistant that lives in your existing chat apps.

The Telegram setup takes about two minutes. Create a bot via @BotFather, copy the token, and add it to your OpenClaw config. Discord follows a similar pattern with a bot token. From there, you can message your agent from your phone and it responds with full tool access, just as if you were sitting at a terminal.

Practical uses include:

• Ask your agent to summarize your email inbox each morning
• Have it monitor a GitHub repo and notify you of new issues
• Request file lookups or document summaries on the go
• Set reminders and calendar events through natural conversation

Because the Pi runs 24/7, your bot never goes offline. Pair it with Fastio's free agent workspace and your bot can store, retrieve, and share files through the conversation. Upload a document to a Fastio workspace, ask your Telegram bot to summarize it using Intelligence Mode, and get cited answers back in the chat.

Best for: People who want a personal AI assistant accessible from any device, anywhere.

Give Your Pi Agents Persistent Storage

Fastio gives OpenClaw agents a shared workspace with built-in RAG, file versioning, and branded shares. 50GB free, no credit card required. Built for raspberry openclaw projects workflows.

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Frigate is an open-source NVR (Network Video Recorder) that runs real-time AI object detection locally. OpenClaw can connect to Frigate and act as the decision layer on top of your camera feeds.

The SwitchBot AI Hub, released in February 2026, was the first hardware with native OpenClaw support and includes Frigate integration. But you can also run Frigate directly on a Pi or a separate machine and connect it to your OpenClaw agent.

With this setup, your agent can:

• Send you a Telegram alert when a person is detected at your front door
• Distinguish between people, packages, pets, and vehicles
• Trigger smart home automations based on camera events (turn on porch lights when someone approaches)
• Log detection events with timestamps for review

All processing happens locally. Your camera feeds never leave your network.

What you need: Raspberry Pi 5, USB camera or IP cameras, Frigate installed (Docker container), and OpenClaw with the Frigate skill.

Best for: Privacy-conscious homeowners who want intelligent camera monitoring without cloud subscriptions.

One of the less obvious but highly practical Pi projects is building a file delivery agent. This works well for freelancers, small studios, or anyone who regularly sends files to clients.

The workflow: your OpenClaw agent watches a designated folder (or a Fastio workspace) for new files. When something arrives, it automatically creates a branded share link and delivers it to the recipient via Telegram, email, or Slack. No manual uploading, no remembering to send the link.

Fastio's MCP server gives OpenClaw agents access to workspace, storage, AI, and workflow operations through Streamable HTTP at /mcp. Your agent can create workspaces for each client, upload files with version tracking, enable Intelligence Mode for automatic indexing, and generate share links with granular permissions. The free agent plan includes 50GB of storage, 5 workspaces, and 50 shares with no credit card required.

You can extend this further with webhooks. Configure Fastio to notify your agent when a client downloads a file or uploads something to a Receive share. The agent can then send you a summary or trigger a follow-up action.

Best for: Freelancers and small teams who want automated, branded file delivery running on cheap hardware.

A Pi running OpenClaw makes an excellent log processing station. Point it at server logs, application logs, or any text-heavy data source and have it produce daily summaries.

Set up a cron job or systemd timer that triggers your agent at a fixed time each day. The agent reads the latest logs, identifies anomalies or important events, and sends you a summary through your preferred channel. For developers managing a few side projects, this replaces the need to check dashboards manually each morning.

You can layer this with file storage for longer-term analysis. Have the agent write each daily summary to a Fastio workspace with Intelligence Mode enabled. Over time, you build a searchable archive of operational history. Ask the workspace "When did we last see a spike in 503 errors?" and get a cited answer pulling from weeks of summaries.

What you need: Raspberry Pi with OpenClaw, access to log sources (SSH, API, or mounted filesystem), and a messaging channel for delivery.

Best for: Solo developers and small ops teams who want automated monitoring without paying for dedicated observability platforms.

Frank's World published a detailed build in March 2026 combining a Raspberry Pi 5 with a 7-inch touchscreen to create a voice-controlled OpenClaw station. The idea: a physical device on your desk that you talk to, and it executes tasks across your digital life.

This project pairs a USB microphone with a speech-to-text engine (Whisper works well on a Pi 5) and routes transcribed commands to OpenClaw. The touchscreen displays the agent's responses and current status. You speak naturally, the agent interprets your request, and it takes action: sending messages, controlling smart home devices, querying files, or running scripts.

The build gets more powerful when you connect multiple services. Combine Home Assistant control with calendar access, email, and file management, and you have a single voice interface for your entire digital workflow.

What you need: Raspberry Pi 5, 7-inch touchscreen, USB microphone, Whisper (or another speech-to-text model), and OpenClaw with relevant skills.

Best for: Anyone who wants a physical AI assistant device rather than a chat window.

Running an AI agent 24/7 on your home network creates a real attack surface. OpenClaw's default configuration binds its gateway to all network interfaces on port 18789 with no authentication. The ModemGuides security setup guide walks through a five-layer hardening approach that turns a basic Pi install into something you can trust.

The layers include:

• VLAN segmentation: Isolate the Pi on its own network segment so a compromised agent can't reach other devices
• Container hardening: Run OpenClaw in Docker with read-only filesystem, no-new-privileges, and port binding restricted to 127.0.0.1
• Gateway lockdown: Add token authentication with 32+ character random strings and use SSH tunnels for remote access
• Host firewall: Default-deny inbound policy with explicit allow rules for SSH and Home Assistant only
• Skill auditing: Only install skills you've reviewed. The guide references a real incident where marketplace skills performed data exfiltration

Additional maintenance practices include monthly gateway token rotation, quarterly API key rotation, and running openclaw security audit to check for known vulnerabilities.

This isn't a separate "project" in the fun sense, but it's essential groundwork for every other project on this list. Skip this step and you're running an agent with shell access, file access, and browser control on an open port.

Best for: Anyone running OpenClaw on a Pi connected to their home network (which is everyone on this list).

The most ambitious project on this list combines several ideas into a single system. Run multiple OpenClaw agents on your Pi, each with a specific role, and have them collaborate through shared file storage.

For example:

• Research agent: Monitors RSS feeds and news sources, saves relevant articles to a Fastio workspace
• Summary agent: Picks up new articles from the workspace, generates briefings, and posts them to your Telegram
• Filing agent: Organizes documents into categorized folders with proper metadata

Fastio's workspace model supports this pattern well. Each agent authenticates with the MCP server and operates on shared workspaces. File locks prevent conflicts when multiple agents access the same files. Intelligence Mode indexes everything automatically, so any agent (or you) can query the workspace using natural language and get cited answers.

When the system produces something useful, ownership transfer lets you hand the entire workspace from the agent account to your personal account. The agent keeps admin access for ongoing maintenance, but you own the data.

The free agent plan at fast.io/pricing includes 50GB storage, 5,000 credits per month, and 5 workspaces. That's enough to run a multi-agent system without paying anything.

Best for: Developers who want to experiment with multi-agent architectures on cheap, always-on hardware.