PMB

Local-first memory for your AI coding agent.

SQLite is the source of truth. No cloud, no API keys, no re-explaining.

Local-first memory, visualized. 3,800+ entities and 41,000+ connections, captured automatically as you work.

Website · Docs · Quickstart · Demo · Why PMB · How it works · FAQ

Your AI agent forgets everything between sessions. So you re-explain the same decisions, lessons and constraints over and over. PMB remembers them in one local workspace and feeds them back through MCP - no cloud, no API keys, no LLM call on the read path. And it tells you when memory is actually helping, instead of claiming "+X%".

⭐ Star the repo if PMB saves you a re-explanation.

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PMB gives Claude Code, Cursor, Codex and the other MCP-aware agents a real memory: decisions you made last week, lessons you taught them, personal facts, project structure, PDFs. They survive every restart, every model upgrade, every agent switch - because they live in a local workspace you own, with SQLite as the durable source of truth and rebuildable search indexes beside it.

No API keys. No subscription. No LLM call on the read path. Just local files.

Quickstart

pip install pmb-ai                 # 1. install
pmb setup                          # 2. detect your agent + wire the MCP entry
pmb warmup                         # 3. preload the model (first recall is instant)
# 4. restart your agent, then just talk to it - memory is automatic
pmb stats                          # 5. see what's stored
pmb recall "auth decision"         # 6. search memory from the terminal
pmb doctor                         # 7. confirm everything is wired

That's it - your agent now remembers. No account, no keys, nothing leaves your machine.

Command name: the CLI is pmb. Via pip you also get the alias pmb-ai; via npm (npx pmb-ai setup) the command is pmb-ai and it installs the Python package first, then runs setup. Same tool - use whichever your install gave you.

Links: pmbai.dev (site) · docs.pmbai.dev (docs) · Getting started · Deleting memories.

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Demo

What it feels like - same prompt, with and without memory:

▶ Click to play the 2-minute setup

You:    fix that LoadGuard pricing bug we hit last Tuesday

Agent:  prepare(message="fix LoadGuard pricing bug")
        ↓ (6 ms)
        → project_context: 12 events about LoadGuard,
          4 lessons (incl. "never lower NEGOTIATE/SKIP under 25%"),
          3 decisions, 2 open goals
        → active_arcs: "LoadGuard verdict-policy refactor (started Tue)"
        → lessons: 1 directly matches "pricing"
        → recent_activity: 8 commits this week

        Looking at src/engine/verdict-policy.ts (you opened it Tuesday
        14:32, last changed Wednesday). The pricing bug is on line 142
        where the bundle fallback tightened below the rate-floor. Per the
        lesson you saved, we never drop the threshold under 25% - restoring
        the guard there.

The agent didn't ask. It didn't guess. It read its memory in 6 ms and showed up already informed.

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Why PMB