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Mem0

Intelligent memory layer for AI agents and assistants

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Mem0 is an open-source intelligent memory layer for AI agents with 51K+ GitHub stars providing persistent, adaptive memory across sessions. It manages working, short-term, and long-term memory types, enabling personalized AI experiences that improve over time. Features automatic memory extraction from conversations, semantic search over stored memories, multi-format support, and integration with 100+ frameworks. Simple API for adding memory to any LLM-powered application or agent.

Mem0 gives AI applications persistent, contextual memory across interactions. With 51K+ GitHub stars, it has become the standard for adding memory to agents, assistants, and chatbots.

Manages working memory, short-term memory, and long-term memory, enabling natural context maintenance. Memory is automatically extracted from conversations and stored with semantic embeddings for efficient retrieval.

Integrates with 100+ frameworks and tools. Both a managed cloud service and self-hosted open-source deployment are available.

Developers add memory to any application with a simple API call, supporting all major LLM providers and vector stores.

Pricing

Free open-source / Mem0 Cloud available

Platforms

Python, API, Self-hosted, Cloud

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Comparisons

Mem0 vs Zep — AI Agent Memory: Vector-First vs Temporal Knowledge Graph in 2026

Mem0 and Zep are the two most-installed memory layers for AI agents in 2026, but they make opposite architectural bets. Mem0 is a fully open-source vector-first memory framework with optional graph memory, ideal for conversational agents and broad ecosystem coverage. Zep is a commercial platform built on Graphiti, a temporal knowledge graph where every fact has a validity window — the right choice when your agent must reason about state that changes over time. This comparison covers benchmarks, temporal reasoning, self-hosting, pricing, and ecosystem fit.

Mem0Zep

Graphiti vs Mem0 — Temporal Knowledge Graphs vs Intelligent Memory Layer for AI Agents

Graphiti builds temporally-aware knowledge graphs that track entity relationships and fact validity over time for AI agents. Mem0 provides an intelligent memory layer that automatically extracts and retrieves relevant context from past interactions. Graphiti wins for complex relationship reasoning while Mem0 wins for quick integration of persistent user memory.

GraphitiMem0

Mem0 vs LangChain — AI Memory Layer vs LLM Application Framework

Mem0 provides a dedicated memory management layer that gives AI applications persistent user context across sessions. LangChain offers a comprehensive framework for building LLM-powered applications with chains, agents, and retrieval pipelines. Mem0 wins for adding memory to existing apps while LangChain wins as a full application development framework.

Mem0LangChain

Supermemory vs Mem0 — Universal AI Memory Platform vs Managed Memory Layer

Supermemory and Mem0 both solve the AI amnesia problem — giving AI assistants persistent memory across conversations. Supermemory offers a complete context stack with RAG, user profiles, connectors, and an MCP server, while Mem0 provides a focused memory layer with simpler API integration. Your choice depends on whether you need a full platform or a lightweight memory component.

SupermemoryMem0