MemMachine
Universal memory layer for AI agents.
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Use cases
About MemMachine
MemMachine is listed in our memory & RAG category and is aimed at builders. Universal memory layer for AI agents. Pricing, as the maker states it: Open source. Maturity: Active. We last checked the official link on 2026-10-16.
What is MemMachine?
MemMachine is an open-source long-term memory layer for AI agents and LLM apps, so they can learn, store and recall information from past sessions.
The project says you can add persistent memory with about five lines of code.
Sources: the official README and our directory listing, checked 2026-10-18. Official site: memmachine.ai.
Who is MemMachine for?
Developers turning stateless chatbots into personalized agents.
MemMachine at a glance
- Open source: Yes (Apache License 2.0)
- GitHub: MemMachine/MemMachine · 3,075 stars (as of Oct 21, 2026)
Key features
- Long-term memory across sessions
- Learn, store and recall
- Quick integration
MemMachine FAQ
What is MemMachine?
MemMachine is an open-source long-term memory layer for AI agents and LLM apps, so they can learn, store and recall information from past sessions.
Who is MemMachine for?
Developers turning stateless chatbots into personalized agents.
Is MemMachine free?
MemMachine's pricing, as the maker states it: Open source. Open-source tools are free to use, though you may still pay for model API usage or a hosted plan. Check the official site for current plans.
Is MemMachine open source?
Yes. MemMachine is released under the Apache License 2.0, according to its GitHub repository.
What are alternatives to MemMachine?
Similar tools include AgentMemory, ReMe, TencentDB-Agent-Memory, Pieces, Acontext and Beacon.
MemMachine ratings and reviews
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MemMachine alternatives
Other memory & RAG tools in our directory. See all memory & RAG tools →
AgentMemory
Persistent memory layer for AI coding agents.
ReMe
Memory management kit for agents.
TencentDB-Agent-Memory
Team-level memory hub that turns conversations, docs and code into shared memory for agents.
Pieces
AI memory layer that captures context from your work so you and your AI tools can recover decisions and resume where you left off.
Acontext
Memory layer that stores agent experience as reusable skills.
Beacon
An open-source memory layer that captures traces from coding agents across harnesses and turns them into self-improving memory and visibility into what your agents did.
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