MemoryAtlas

TencentDB Agent Memory

Tencent

Fully-local long-term memory for AI agents built on two pillars: layered long-term memory (a semantic pyramid L0 Conversation -> L1 Atom -> L2 Scenario -> L3 Persona) and symbolic short-term memory that offloads verbose tool logs to files while keeping a compact Mermaid 'canvas' in context. Distributed as a TypeScript/npm package (@tencentdb-agent-memory/memory-tencentdb); integrates with OpenClaw and Hermes via plugins and exposes a REST Gateway API at port 8420 for use from any HTTP-capable agent framework.

Storage
Dual-layer heterogeneous storage: bottom layers (atomic facts, logs, raw tool outputs as refs/*.md, step summaries as jsonl) persist in SQLite + sqlite-vec for full-text and vector retrieval; top layers (personas, scenes, Mermaid canvases) are stored as human-readable Markdown. A deterministic node_id drill-down path links each abstraction back to ground-truth evidence. Optional Tencent Cloud Vector Database (TCVDB) backend available via migration script.
Retrieval
Hybrid retrieval: BM25 + vector + RRF (ranked reciprocal fusion) over the stored layers, supporting both keyword and semantic recall. Hierarchical recall: the agent attends to the top-layer Persona/canvas in context and drills down to mid-layer indexes (Scenario/jsonl) and bottom-layer raw text (L0/refs) via node_id when detail is needed.
Self-host
Self-host: moderate
License
MIT
Pricing
Open-source (MIT), free to self-host; fully local with zero external API dependencies. · Free / OSS
GitHub stars
19,196
Last release
2026-08-03
Last commit
2026-08-10
First catalogued
2026-06-28

Strengths

  • Layered design (L0->L3 semantic pyramid) avoids flat vector dumps and preserves a traceable drill-down path back to source evidence
  • Symbolic short-term memory (Mermaid canvas + history offloading) targets token reduction on long-horizon tasks
  • Hybrid retrieval (BM25 + vector + RRF) supports both keyword and semantic recall within the same pipeline
  • REST Gateway API at port 8420 makes the memory layer callable from any HTTP-capable agent framework, not just OpenClaw or Hermes
  • Fully local with no external API dependency; backed by Tencent

Watch out

  • Young project (created 2026-04) — the API and storage surface may still be moving
  • License: README badge says MIT and package.json confirms MIT, though GitHub auto-classifies it 'NOASSERTION' (non-standard header in LICENSE file)
  • Requires Node.js 22.16 or later — strict minimum version barrier for npm users
  • README carries self-reported benchmark numbers (WideSearch, SWE-bench, AA-LCR, PersonaMem) — record those via harvest-benchmarks with selfReported:true, not on this card

Best for

  • Long-horizon agent tasks needing token-efficient, fully-local memory with traceable layered recall
  • Agents running on OpenClaw or Hermes wanting zero-config long-term memory with no external API
  • Teams that want a standalone REST Gateway memory sidecar callable from any agent framework

How it integrates

Benchmark results

No sourced results yet.

Sources

Last verified 2026-08-01 · updated by refresh-framework-cards