AI Agents
A-mem-sys
Agentic memory for LLM agents, from a published research project.
★ 401 starsMIT
View guide →Research-backed lifelong memory for LLM agents, text and multimodal.
SimpleMem is an open-source ai agents project by aiming-lab (aiming-lab/SimpleMem on GitHub). It has 3,823 GitHub stars and 402 forks, is released under the MIT license, and was last updated on GitHub on 24 July 2026.
Decide what you want the project to do before installing anything.
Grab the source and skim the README for setup requirements.
Install dependencies and add any API keys or settings it needs.
Launch it and follow the example workflow from the docs.
Designed for very long horizons.
Handles text and other modalities.
Compression keeps memory tractable.
Tied to an ICML 2026 paper.
Structured memory representation.
Free to build on.
Download the source and move into the project folder.
git clone https://github.com/aiming-lab/SimpleMem.git
cd SimpleMemCreate a virtual environment and install the requirements.
python -m venv .venv && source .venv/bin/activate
pip install -r requirements.txtTreat these as starting points - the README documents the exact commands.
python examples/quickstart.pyIt is an open-source project at aiming-lab/SimpleMem with 402 forks. Check the repo's contributors and recent commits to judge how active maintenance is.
Yes - it is MIT licensed, so you can use, modify, and distribute it freely, including in commercial projects.
It depends on your setup - self-hosted storage can be free, while hosted tiers or embedding APIs may cost money. Check the README for options.
SimpleMem is a research system with a paper to read; mem0 and cognee are production-oriented platforms. Choose SimpleMem to study and extend the ideas, the others to ship memory features.
Clone the repo, read the README's quickstart, and run the provided example - most projects get you to a first result in minutes.
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