TencentCloud/TencentDB-Agent-Memory

It solves the problem of agents repeatedly re-learning context, documents, and workflows in new sessions, which wastes tokens and time. Unlike simple conversation memory, it provides structured, reusable memory assets (skills, wikis, code graphs) that are shared across agents and frameworks, enabling team-level knowledge accumulation and cold-start from existing experience.

Developers can build AI agent teams that continuously learn and improve, with shared memory of user preferences, project context, and proven workflows. Use cases include automated code refactoring with awareness of legacy constraints, document-based Q&A systems that avoid re-reading, and multi-agent collaboration where each agent contributes to a growing knowledge base. The ceiling includes full lifecycle memory management, cross-framework portability, and integration with tools like Claude Code and OpenClaw.