MOM (Memory Oriented Machine), from Momhq, is a persistent memory engine for AI coding agents that helps retain project decisions and constraints across sessions. The tool captures architectural choices and conversational context into a local project store and makes that history accessible to AI runtimes through standard file interfaces. Key attributes include local-first persistence, readable project history, and automatic capture of agent transcripts. Engineers who use coding assistants gain durable, inspectable context across tool switches and restarts.

What tasks MOM reliably handles for developer workflows

MOM focuses on keeping engineering intent available so agents avoid repeated re-explanations. The system preserves context across '/clear' commands, agent restarts, and tool switches by recording decisions, conventions, and constraints into an append-only ledger and folding conversational transcripts into the project vault. That persistence reduces the need to re-specify architectural rationale during successive code-generation or review sessions with different assistants.

Retrieval follows a flat-file, zero-query model rather than a query server

The developer replaced a database-backed vault with plain documents to simplify access. Rather than serving queries, the memory engine projects history into discrete files that agents read with their native file tools. Continuous recording watches supported harness transcripts and folds them into discrete documents, so recent interactions appear as readable artifacts an agent can consult during code generation and review tasks.

Platform and installation choices align with developer toolchains

MOM targets CLI-oriented setups on macOS and Linux. Recommended installation methods include Homebrew or building from source on GitHub. The tool lists integrations with common AI harnesses such as Claude Code, Codex, Pi, and Windsurf. Those choices let engineering teams add a persistent memory layer to existing agent harnesses without deploying a separate query server infrastructure.

Local storage preserves data locality but needs team policies

All memory is stored locally in an append-only ledger and a per-project vault. The ledger and projected files keep history on developer machines rather than remote services, which supports privacy and control. Because recording is continuous and the files are human-readable, teams should decide how to back up, share, or omit vault files to match repository, audit, and privacy practices.

A pragmatic, developer-focused memory layer in active development

MOM is a practical choice for software engineers who need durable, inspectable project context; it is currently in public alpha (v0.50.0-alpha) and the project dogfooded itself, producing thousands of memory documents during development. Expect active iteration and plan for hands-on setup and validation of stored memories before relying on them in high-stakes workflows.