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Open-Source Agent Memory Frameworks: Seven Contenders and a Selection Guide

Seven open-source memory frameworks span the spectrum from auto-extracted vectors to human-readable files: Mem0's one-line add(), Graphiti's bi-temporal knowledge graph, Letta's agent-edited system-prompt blocks, LangGraph's namespaced Store, LlamaIndex's priority-based block truncation, Cognee's triple-store pipeline, and Supermemory's temporal vector-graph engine. This post compares their storage, write/forget mechanics, tenant isolation, and benchmark numbers, then offers selection guidance for four common scenarios.

Mem0 Complete Guide: Controlled Long-Term Memory for AI Agents

Mem0 sits between an agent and storage: it extracts durable facts from interactions, scopes them by user, agent, or run, and searches them before a later generation. Its appeal is a small API; its risks are extraction errors, stale memories, and authorization boundaries.