Mnemosyne

Version control for AI agent memory.

An AI agent builds up memory as it works: facts it learns, decisions it makes. Frameworks store that as state it overwrites as it goes. Mnemosyne gives agent memory what Git gives code: commits, branches, merge, blame and bisect. A Rust core, a mnem CLI, and a Python SDK. Local, deterministic, no network, no model calls.

This is the reference documentation. For the project overview, the quickstart and the demo, see the README on GitHub.

What is here

• On-disk format: the .mnem/ store, specified in enough detail to write a reader in another language. Final for Era 1 at format_version 1.
• Benchmark report: what the substrate delivers, measured. Reconstruction, bisect precision, blame accuracy, merge correctness, and the overhead against a dict and a JSONL log.
• Merge chaos report: the merge invariants over a 50,000-case seeded sweep.
• Architecture decisions: every decision that shaped Mnemosyne, and why it went the way it did. Accepted before the code.
• Research: the surveys that fed the decisions.
• Progress notes: what shipped in each release, in plain language.

Use the sidebar.

The three eras

1. The substrate (now, 0.0.x): single-agent versioned memory. Local and deterministic.
2. The collaboration layer: semantic merge that reasons about contradiction, a sync protocol between stores, and a review step. Pull requests, for agent memory.
3. The platform (1.0): the whole agent as one versioned, signed, forkable artefact, with a registry. The GitHub for AI agents.

See ADR-0010.