You can set up OpenClaw(Moltbot/Clawdbot) on a Raspberry Pi as long as the device supports the required Node.js runtime and has sufficient resources for your intended workload. Raspberry Pi devices are commonly used for always-on, low-power services, which makes them attractive for running a personal AI agent. The setup process is similar to installing on any Linux system, with additional attention paid to CPU architecture and memory constraints.
Typically, you install a Linux-based operating system on the Raspberry Pi, install a compatible Node.js build for ARM, and then install OpenClaw(Moltbot/Clawdbot) using the standard method. Because Raspberry Pi hardware is limited compared to desktops or servers, most users configure OpenClaw(Moltbot/Clawdbot) to use hosted AI models rather than running large local models directly on the device. In this configuration, the Raspberry Pi acts as the orchestration and messaging hub, while heavy inference happens elsewhere.
For features that require long-term memory or document retrieval, it is common to externalize storage. Instead of storing embeddings locally on the Raspberry Pi, you can connect OpenClaw(Moltbot/Clawdbot) to a vector database such as Milvus or managed Zilliz Cloud. This keeps the Raspberry Pi lightweight while still enabling semantic search and persistent memory. With this design, the Pi can be replaced or upgraded without losing historical context.