AI Topic: Agent Memory
Memory layers, frameworks, and services that enable AI agents to store, recall, and manage information across sessions. These tools provide persistent, semantic, and contextual memory for agents, supporting personalization, long-term context retention, graph-based relationships, and hybrid RAG + memory workflows.
AI Tools in Agent Memory (5)
LangMem
6hOpen-source SDK from LangChain for long-term memory in LLM agents, with hot-path tools, a background memory manager, and native LangGraph storage integration.
Letta
6hOpen-source platform for stateful AI agents with persistent memory. Build, observe, and deploy agents via ADE, REST API, SDKs, and a desktop app. Connect tools via MCP; use any model; run self-hosted or on Letta Cloud.
Zep
6hContext engineering platform that gives AI agents long-term memory via a temporal knowledge graph, Graph RAG, and context assembly. SDKs for Python/TS/Go, MCP server support, and usage-based pricing.
Mem0
6hMemory layer for AI apps and agents. Open-source SDK + managed API that adds long-term, semantic and graph memory with fast retrieval, policy controls, and analytics.
Supermemory
1moA developer-friendly memory API with semantic search and content ingestion for building AI apps that remember.
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