mem0ai/Mem0
Universal memory layer for AI Agents
Mem0 is an open-source memory layer for AI agents and assistants that lets them remember facts about users and past conversations across sessions. It extracts, stores, and retrieves long-term memories so your agent stays personalized and consistent instead of starting cold every time.
Our Review
Mem0 has 57,000 GitHub stars as one of the most-adopted ways to give AI agents long-term memory. The problem it solves is familiar: most LLM apps forget everything between chats, so Mem0 sits alongside your agent, learns what matters about each user, and feeds the right memories back at the right moment.
What Mem0 does:
- •Long-term agent memory automatically extracts and stores key facts from conversations, so agents recall them later.
- •Personalization remembers each user's preferences, history, and context to make responses feel continuous.
- •Smart retrieval surfaces only the relevant memories for a given query, keeping prompts small and focused.
- •Works with any stack SDKs for Python and TypeScript, and it plugs into OpenAI, Anthropic, LangChain, and more.
- •Pluggable storage back memories with vector, graph, and key-value stores you choose.
- •Open source or hosted self-host the library, or use the managed Mem0 Platform for production scale.
Getting started:
Install with pip install mem0ai (or the npm package), initialize a memory client, and call add() to store and search() to retrieve. Docs at docs.mem0.ai.
Limitations:
Mem0 is a developer library, so you wire it into your agent code rather than getting a finished product. What it remembers is only as good as how you configure extraction, and storing personal data brings privacy and retention responsibilities you must handle. Production scale and advanced features lean on the paid Mem0 Platform, and memory adds LLM and storage calls that have a cost.
Our Verdict
Mem0 is one of the most popular open-source answers in 2026 to the problem that AI assistants forget everything. If your agent or chatbot needs to remember users across sessions and feel personalized rather than stateless, Mem0 is a well-supported place to start, with 57,000 stars and an Apache-2.0 license.
For developers, Mem0 drops into an existing agent with a small API: add memories from conversations and search them at query time, backed by the vector or graph store you prefer. SDKs for Python and TypeScript and integrations with common frameworks mean it fits most stacks without a rewrite.
Skip Mem0 if your app is stateless by design or a simple conversation buffer is enough; adding a memory layer is extra moving parts and cost. If you want a fuller agent framework with memory built in, Letta takes a more all-in-one approach than a dedicated memory library.
Frequently Asked Questions
What is Mem0?
Mem0 is an open-source memory layer for AI agents and assistants, from the mem0ai team. It automatically extracts important facts from conversations, stores them, and retrieves the relevant ones later, so an agent can remember users, preferences, and past context across sessions. It offers Python and TypeScript SDKs and a managed platform.
Is Mem0 free and open source?
Yes. Mem0 is released under the Apache-2.0 license and is free to use as a self-hosted library as of 2026. The mem0ai team also offers a managed Mem0 Platform with free and paid tiers for production scale. The costs you take on when self-hosting are the LLM and storage calls used to build and query memory.
How does Mem0 work?
Mem0 sits between your app and its LLM. As conversations happen, it uses a model to extract salient facts and writes them to a store, such as a vector or graph database. At query time it retrieves only the memories relevant to the current request and adds them to the prompt, so the agent stays personalized without bloating context.
How is Mem0 different from a vector database?
A vector database stores and searches embeddings but does not decide what is worth remembering. Mem0 is a memory layer on top: it extracts which facts matter, updates or supersedes them over time, and retrieves them for the agent. Choose a plain vector store for raw retrieval; choose Mem0 when you want managed, evolving agent memory.
What can I build with Mem0?
Mem0 is used to add long-term memory to chatbots, customer-support agents, personal assistants, and autonomous agents as of 2026. It lets those systems remember a user's preferences, prior issues, and context across sessions, which makes them feel continuous and personalized. You integrate it through its SDK and pair it with your existing models and storage.
How do I install Mem0?
Visit the GitHub repository at https://github.com/mem0ai/mem0 for installation instructions.
What license does Mem0 use?
Mem0 uses the Apache-2.0 license.
What are alternatives to Mem0?
Explore related tools and alternatives on My AI Guide.
Open source & community-verified
Apache-2.0 licensed: free to use in any project, no strings attached. 57,619 developers have starred this, meaning the community has reviewed and trusted it.
Reviewed by My AI Guide for relevance, quality, and active maintenance before listing.
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