# mem0ai/mem0

> The Memory Layer for AI Agents - Drop-in memory infrastructure for AI agents and apps. Context that persists. Built for production.

- GitHub: https://github.com/mem0ai/mem0
- Website: https://mem0.ai
- Category: RAG, Search & Data (https://ideas.asveas.com/c/rag); also AI Agents
- Tags: agentic-memory, agentic-memory-system, ai-agents, ai, chatgpt, genai, llm, long-term-memory, memory, memory-management, python, rag, state-management, openai
- Language: Python · License: Apache-2.0
- Stars: 68,817 · Forks: 8,187 · Open issues: 933
- Last push: 2026-11-06 (5 days ago)
- Vibe score: 94/100

## What it is
All benchmarks run on the same production-representative model stack. Single-pass retrieval (one call, no agentic loops) at a top_200 retrieval budget. Scores reflect Mem0's managed platform, which includes proprietary optimizations not available in the open-source SDK; open-source users should expect directionally similar gains but not identical numbers.

## When to use it
Reach for mem0 when you need semantic search, embeddings, scraping or turning documents into LLM-ready data — it's written in Python and fits stacks tagged agentic-memory, agentic-memory-system, ai-agents, ai.

## Maintenance
mem0ai/mem0 looks very actively maintained: the last push was 5 days ago (2026-11-06), with 68,817 stars and 933 open issues.

## Quick start
```bash
git clone https://github.com/mem0ai/mem0.git
```

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Source: https://ideas.asveas.com/r/mem0ai/mem0 · Catalog: https://ideas.asveas.com/llms.txt
