"I built a portable memory layer for AI agents so you don't have to"

A developer has built Mneme, a portable memory layer for AI agents that goes beyond simple vector database storage. Mneme provides structured memory types (episodic, semantic, procedural), semantic recall using local embeddings, consolidation, forgetting with audit trails, and portability via .mneme files. The tool is local-first with a SQLite backend and supports multi-agent access control.

markdown I built a portable memory layer for AI agents so you don't have to AI agents are everywhere now. But they still struggle with one thing: memory . Most agent frameworks store memory in a vector database, but that's not enough. A vector DB just stores embeddings; it doesn't understand memory types, consolidation, forgetting, or portability. So I built Mneme — a portable memory layer for AI agents. What does Mneme do? - Structured memory : episodic what happened , semantic facts/preferences , procedural how to behave . - Semantic recall : find relevant memories using local embeddings FastEmbed . - Consolidation : deduplicate and summarise memories over time. - Forgetting : delete memories with full audit trail. - Portability : export/import your agent's entire memory to a .mneme file. - Access control : multi‑agent scoping with explicit shared memory grants. - Local‑first : SQLite backend, zero‑config. Installation