Mem0 and LangMem both add long-term memory to agents, but from different starting points. Mem0 is a standalone memory layer you can use anywhere. LangMem is LangChain's memory tooling, most at home inside a LangGraph app. If you're already all-in on LangChain, that gravity matters; if you're not, a framework-agnostic layer keeps you portable. (Looking at the whole field? See our roundup of the best memory for AI agents.)
Mem0 vs LangMem at a glance
| Mem0 | LangMem | |
|---|---|---|
| Home turf | Framework-agnostic | LangChain / LangGraph |
| Lock-in | Low | Tied to the LangChain stack |
| Shines at | Any agent, any framework | Memory inside LangGraph apps |
| Documents / RAG | Not the focus | Via LangChain retrievers |
When to choose Mem0
Choose Mem0 if you want memory that isn't tied to one framework, so you can switch orchestration later without ripping out your memory layer.
When to choose LangMem
Choose LangMem if your app already lives in LangGraph and you want memory that slots into that ecosystem natively.
Where Kit for AI fits
Either way, memory is only half the retrieval story. Kit for AI adds document ingestion and hybrid search alongside remember/recall, and it's framework-agnostic — call it from LangGraph, CrewAI, a script, or over MCP. See our guide to persistent memory for LangGraph for the wiring.
Related reading
Go deeper: persistent memory for LangGraph · the AI memory API — or start with the complete guide to persistent memory for AI.
Want memory that reads your documents too, across every tool you use? Start free and connect over MCP or the REST API.