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A curated list of tools that help AI agents and chats avoid starting from scratch: storing project rules, sources, decisions, chat history, codebase context and important facts for future sessions.
A curated list of tools that help AI agents and chats avoid starting from scratch: storing project rules, sources, decisions, chat history, codebase context and important facts for future sessions.
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It is the data layer around the model: user facts, project rules, past decisions, documents, codebase context and action history. It helps an agent continue work instead of relearning the same information every session.
A knowledge base usually stores documents for human search or chatbot answers. These tools focus on agents: injecting relevant context into a task, updating memory after work and linking facts to actions.
For code and engineering knowledge, look at Driver, ContextClue, Convolut, Kimi Work and Graphlit. For memory inside your own AI apps, start with Mem0, Zep, Cognee and MemoriPy.
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