Mnemon

Mnemon

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LLM-supervised persistent memory for AI agents.

LLM agents forget everything between sessions. Context compaction drops critical decisions, cross-session knowledge vanishes, and long conversations push early information out of the window.

Mnemon gives your agent persistent, cross-session memory — a four-graph knowledge store with intent-aware recall, importance decay, and automatic deduplication. The mnemon memory path remains one local binary with zero API keys and one setup command.

Mnemon ships one executable with two separate surfaces. Memory stays at the
mnemon root; Agency Preview lives at mnemon agency ... and adds
durable, project-local responsibility and effect admission to an existing Pi
agent. Agency does not replace Memory or the Agent Runtime.
Claude Max / Pro subscriber? Mnemon works entirely through your existing subscription — no separate API key required. Your LLM subscription *is* the intelligence layer. Two commands and you're done.

Why Mnemon?

Most memory tools embed their own LLM inside the pipeline. Mnemon takes a different approach: your host LLM is the supervisor. The binary handles deterministic computation (storage, graph indexing, search, decay); the LLM makes judgment calls (what to remember, how to link, when to forget). No middleman, no extra inference cost.

Mnemon also addresses a gap in the protocol stack. MCP standardizes how LLMs discover and invoke tools. ODBC/JDBC standardizes how applications access databases. But how LLMs interact with databases using memory semantics — this layer has no protocol. Mnemon's three primitives — remember, link, recall — form an intent-native protocol: command names map to the LLM's cognitive vocabulary (remember not INSERT, recall not SELECT), and output is structured JSON…