Write: while working, PMB stores facts, decision, and learnings on MCP (automatically using hooks). Everything is saved to SQLite, gets embedded, and the entities get linked to a graph.

Read: before answering the prompt, a hook does a search (BM25 + embedding + entities graph using RRF) and provides the best matches. No manual recall required.

All on-premises: SQLite + LanceDB, embedder on-premises, and optionally Ollama.