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cmoraes10/loci

Typed long-term memory for AI agents. One core, an MCP server, and a Hermes plugin.

⭐ 27 stars
⑂ 0 forks
Python
momentum ▲ 45.0
created 2026-10-01
on radar since 2026-10-01
star trend 9 → 27 since 2026-10-01
agent-memoryai-agentshermesllmlong-term-memorymcpmcp-servermemorymodelmodel-context-protocolopen-sourcepythonsqlite
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About loci

Typed long-term memory for AI agents. One core, two adapters.

The name comes from the method of loci, the ancient memory palace technique where every recollection gets a place and a structure. That is the thesis of this project.

An agent that forgets you every session is a search box with manners. This is the layer that fixes that: durable facts about a person, typed and ranked, extracted from the conversation rather than typed into a settings page, consolidated daily so the list does not rot.

Ported from the memory system running in production in Lima, rewritten host-agnostic.

Eight categories (routine, study, preferences, finance, goals, relationships, constraints, ephemeral), four importance tiers, a status lifecycle. A preference and a deadline are not the same kind of thing and do not age the same way.

Extraction runs on two paths. A model reads the exchange for meaning; regex heuristics catch the phrasings you wrote them for. Merged with model precedence. When the provider is down the regex path still runs.

A write filter keeps the store from becoming a mood diary. Passing mood is the case it exists for. "Tired today" is true for hours and wrong for months.

The injection cap keeps context from growing without bound. Twelve facts reach the model, ranked by importance and then by deadline proximity and recency.

Daily consolidation and decay keep the list honest. Exact duplicates merge; guesses nobody confirmed expire on their own; ephemeral facts carry a 24-hour TTL; completed goals expire after 90 days.

From the project README.

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