TencentDB Agent Memory: A fully local 4-tier long-term memory system for AI agents with zero external API dependencies
Summary
TencentDB Agent Memory is an open-source project from Tencent Cloud that provides fully local long-term memory for AI Agents through a 4-tier progressive pipeline with zero external API dependencies. It combines symbolic short-term memory with layered long-term memory, and when integrated with OpenClaw, it reduces token usage by up to 61.38%, improves pass rate by 51.52%, and boosts PersonaMem accuracy from 48% to 76%. The system uses a four-tier architecture: Short-term Memory (STM), Personal Memory (PM), Episodic Memory (EM), and Semantic Memory (SM), each with specific functions and benchmarks. The project is MIT-licensed and available on GitHub.
Source
Twitter / XTencentDB Agent Memory: A fully local 4-tier long-term memory system for AI agents with zero external API dependenciesgithub.comKey quotes
· 3 pulledWhen integrated with OpenClaw, it cuts token usage by up to 61.38%, improves pass rate by 51.52% (relative), and raises PersonaMem accuracy from 48% to 76%.
TencentDB Agent Memory = symbolic short-term memory + layered long-term memory.
TencentDB Agent Memory delivers fully local long-term memory for AI Agents via a 4-tier progressive pipeline, with zero external API dependencies.
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