Mem0

Overview

Mem0 solves the biggest limitation of AI agents: they forget everything between sessions. With Mem0, your agents remember user preferences, past conversations, learned facts, and contextual information — creating truly personalized experiences. With 51k+ GitHub stars, it’s the most popular memory solution in the AI ecosystem.

How It Works

1. Add memories — Store facts and preferences from conversations
2. Auto-extract — Mem0 automatically identifies important information
3. Retrieve — When new conversations start, relevant memories surface
4. Evolve — Memories update as information changes

Use Cases

• Personal assistants — Remember preferences, habits, history
• Customer support — Recall past tickets and account context
• Education — Track student progress and learning style
• Sales — Remember prospect interactions and relationship context

Getting Started

from mem0 import Memory
m = Memory()

m.add("I prefer dark mode and vim keybindings", user_id="alice")
results = m.search("What IDE settings?", user_id="alice")
# Returns: "User prefers dark mode and vim keybindings"

Example

Session 1: User says "I'm working on Next.js 14 with TypeScript"
Agent stores this in Mem0.

Session 2 (next day): User asks "How do I add auth?"
Agent → Mem0 → Retrieves: "User's project: Next.js 14 + TypeScript"
Agent: "Since you're using Next.js 14, use NextAuth.js v5 with App Router..."
(Remembers context without being told again)

Alternatives

• Zep — Memory with temporal awareness
• LangChain Memory — Built-in modules (simpler, less persistent)
• MemGPT/Letta — Self-editing memory with virtual context