TencentCloud/TencentDB-Agent-Memory
An open-source memory hub turns agent conversations, workflows, docs, and code into governed assets that can be reused across sessions and roles, reducing repeated project setup.
TencentDB Agent Memory packages prior work into **four memory assets**: Chat Memory, Skills, Wiki, and CodeGraph. The hub adds ownership, versions, agent bindings, and private, team, or ACL-based access.
Use it to give coding and review agents different context loadouts instead of one global prompt. Memory is distilled through **L0–L3**, while detailed recall combines **BM25, vector retrieval, and RRF** under context-size and timeout limits.
TencentDB Agent Memory packages prior work into **four memory assets**: Chat Memory, Skills, Wiki, and CodeGraph. The hub adds ownership, versions, agent bindings, and private, team, or ACL-based access. Use it to give coding and review agents different context loadouts instead of one global prompt. Memory is distilled through **L0–L3**, while detailed recall combines **BM25, vector retrieval, and RRF** under context-size and timeout limits. The Team Memory release is still a beta. Wiki and CodeGraph indexing is asynchronous, private-repository support and automatic routing remain incomplete, and current compatibility is limited to **OpenClaw, Hermes, and SDK integrations**.
This turns the proposed shared context layer into a concrete, permissioned asset hub with agent-specific loadouts, versioning, distilled levels, and bounded hybrid retrieval. It broadens memory beyond chat history to skills, documentation, and code structure, while narrowing near-term adoption through beta status, asynchronous indexing, incomplete routing and private-repository support, and limited integrations.