Back to directory

Mnemon

A single local binary that gives AI agents persistent, cross-session memory as a graph-based store, with intent-aware recall, importance decay and automatic deduplication, supervised by the host LLM rather than an embedded model.

Mnemon

Mnemon stores memory as a four-graph knowledge store and exposes three primitives, remember, link and recall, as an intent-native protocol for how an LLM interacts with a memory database, with structured JSON output rather than raw rows. The binary handles deterministic computation such as storage, graph indexing, search and decay, while the host LLM decides what to remember, how to link it and when to forget it, with no extra inference cost from an embedded model.

It ships one executable with two surfaces: memory operations at the mnemon root, and an optional "Agency Preview" at mnemon agency that adds durable, project-local responsibility and effect admission to an existing Pi agent, without replacing memory or the underlying agent runtime.

It works with DeepSeek Harness, Claude Code, OpenClaw and other agent runtimes, needs no API keys, and is written in Go.

More in Agent memory

See all 450
  • A long technical guide to AI agent memory: why stateless LLMs need it, the different memory architectures from vector stores to knowledge graphs, and how Cognee implements one as an open-source memory layer.

  • A local, file-based long-term memory layer for a personal AI that never summarizes conversations, keeping every line with a timestamp and searching by time first and words second, rather than retrieving only similar-seeming chunks.

  • NEOTH

    deepwiki.com

    A local-first personal AI daemon in Rust with five memory tiers, consent-gated tools, a WASM plugin sandbox, multi-provider model routing and signed audit logs, aimed at people who want both a daily assistant and a serious coding helper.