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EN-B006-007-raspberry-pi-memory

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[EN-B006-007] Persistent Semantic Memory on Raspberry Pi 5

  • Date: 2026-02-14
  • Language: EN
  • Category: Infrastructure / Knowledge Base
  • Status: Advanced Deployment

💡 Core Concept​

Building a self-contained AI agent on a Raspberry Pi 5 that uses local Qdrant (vector database) and MCP (Model Context Protocol) for persistent, semantic memory without any cloud storage.

🛠️ Implementation Details​

  • Agent/Model: Flexible (Cloud orchestrator with local vector store)
  • Tools Used: Raspberry Pi 5, Qdrant, mcporter skill, file-system
  • Key Workflow:
    1. Install OpenClaw and Qdrant on a Raspberry Pi 5.
    2. Use the mcporter skill to connect the agent to the local vector database.
    3. Every interaction is summarized and embedded into the local store.
    4. Subsequent queries use semantic search to retrieve relevant history (approx. 3s latency per query).

🌟 Unique Value / Insight​

Allows for a "Forever Agent" that resides on low-power, dedicated hardware. This setup provides long-term continuity that survives provider switches or internet outages, ensuring your personal history is always accessible and private.

🏷️ Tags​

#OpenClaw #RaspberryPi #VectorDB #LocalMemory #MCP #SelfHosted