memnet-llm provides an in-memory working-memory graph as a CLI tool for LLM agents. It acts as a goldfish-brain scratch space, allowing agents to store, retrieve, and reason over structured knowledge during conversations or tasks. Designed for developers building autonomous AI agents that need reliable short-term memory without external databases.
In the AI & ML space, memnet-llm takes a focused approach. LLM agents forgetting context and lacking persistent working memory during long interactions. memnet-llm is an open-source project aimed at developers. The project is open source (MIT). It runs on the command line.
It is developed by Chou Swei, and the product first shipped in 2026. The project is developed in the open on GitHub with 70 commits in the last 90 days. Among its 3 catalogued features are Working Memory Graph, In-memory Knowledge Store, and Agent Memory.
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