Your agents forget. Neotoma makes them remember.

# Neotoma > Deterministic state layer for long-running AI agents ## What it does Neotoma is an open-source deterministic state layer for AI agents. It uses append-only observation logs, hash-based entity IDs, and schema constraints to give agents versioned, reproducible, auditable memory that never silently mutates. Same observations always produce the same entity state. ## Key facts - Open-source, MIT-licensed - Installs via npm: `npm install -g neotoma` - Interfaces: REST API, MCP server, CLI - Platforms: macOS, Linux, Windows (WSL) - AI tool integrations: Cursor, Claude, Claude Code, ChatGPT, Codex, OpenClaw - Local-first: data stays on your machine, no cloud sync, no telemetry - Written in TypeScript, backed by SQLite ## Core guarantees - Deterministic state evolution: same observations always produce the same entity state - Versioned history: every change creates a new version, earlier states preserved - Replayable timeline: replay observations to reconstruct any historical state - Auditable change log: every modification records who, when, and from what source - Schema constraints: entities validated against defined types, malformed writes rejected - Silent mutation prevention: no overwrites, merges, or drops without a trace - Conflicting facts detection: contradictory statements detected and resolved deterministically - Reproducible state reconstruction: rebuild complete state from raw inputs alone - Human inspectability: diff any two versions, trace every fact to its origin ## Key concepts - Entity: canonical representation of a person, company, task, or object with deterministic ID - Observation: immutable, timestamped fact about an entity; never modified or deleted - Snapshot: current truth for an entity, computed by merging all observations via reducers - Reducer: deterministic function that merges observations into a snapshot - Provenance: origin tracking so every value traces back to its source - Memory graph: the graph of sources, observations