Lemmalog

Lemmalog is a Datalog engine for LLM-agent memory, distributed as a Rust crate with an MCP server, REPL, and agent skill. It treats extracted statements as provenance-tracked base facts, then uses runtime-parsed stratified Datalog to derive temporal projections, closures, contradiction candidates, relevance relationships, and aggregates. The engine supports seminaive incremental fixpoint evaluation, stratified negation with negative-cycle rejection, bi-temporal facts, confidence and provenance annotations, proof trees through why(), scoped retraction recomputation, demand-driven ask_deep queries using magic sets, and persistence of episodes, rules, and base facts while rebuilding derived relations on load. Its AgentMemory facade connects an extractor to deterministic ADD, UPDATE, NOOP, and escalation policies, and assembles budgeted contexts from distilled facts and their source episodes. The MCP server exposes the engine to agent harnesses such as Claude Code and Kimi CLI through tools for observing facts, querying, explaining proofs, retrieving context, saving state, installing rules, and running hypotheticals.