Agent Recall
Correction-first agent memory with a precision KPI that tracks whether agents heed warnings, across 5 local-only layers.
Agent Recall implements correction-first memory for AI agents, prioritizing explicit corrections in a 5-layer local memory architecture. A precision KPI measures whether agents acknowledge and act on stored warnings. All data stays local with no cloud dependency.
Source
Repository: https://github.com/goldentrii/agentrecall-mcp/tree/HEAD/packages/mcp-server
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