PMB

PMB is a local-first memory layer for AI coding agents that keeps decisions, lessons, and project facts in a single SQLite file on a developer’s machine. It plugs into MCP-aware tools like Claude Code, Cursor, Codex, Zed, and Windsurf so each agent shares the same long-term context across sessions. By recalling relevant snippets in roughly 35 milliseconds and writing updates asynchronously, it gives AI assistants persistent project awareness without any cloud, telemetry, or API keys.

What is PMB? PMB is a local-first memory layer for AI coding agents that keeps decisions, lessons, and project facts in a single SQLite file on a developer’s machine. It plugs into MCP-aware tools like Claude Code, Cursor, Codex, Zed, and Windsurf so each agent shares the same long-term context across sessions. By recalling relevant snippets in roughly 35 milliseconds and writing updates asynchronously, it gives AI assistants persistent project awareness without any cloud, telemetry, or API keys. Key Features: Local-first persistent memory: Stores all events in SQLite with vectors in LanceDB on disk, so agents read and write project memory without data leaving the machine. Automatic hybrid recall: Classifies every message in under a millisecond, then uses BM25, dense vectors, and an entity graph with reciprocal-rank fusion to fetch useful context before the model answers, with reported recall@10 of 94. 6 percent on the LoCoMo dataset. Low-latency reads and async writes: Recall typically lands in tens of milliseconds, while writes return in under 1 millisecond as embeddings and vector inserts run on a background thread. Map and Timeline dashboard: A local web app shows a live entity graph and git-style timeline of decisions, lessons, commits, and facts so developers can inspect and clean up memory.