hivemind vs TencentDB-Agent-Memory
Activeloop's shared brain for agent TEAMS: traces from Claude Code, Codex, Cursor & co become reusable skills every teammate's agent can execute — cloud-backed, 25% cheaper on LoCoMo. — versus — Tencent's team memory hub for agents: an API proxy turns conversations, docs and code into shared chat memory, skills, an LLM wiki and a code graph, reused across agents.
Both are a shared brain for agent teams that turns traces from many harnesses into reusable knowledge and skills.
| hivemind | TencentDB-Agent-Memory | |
|---|---|---|
| Stars | 1.6k | 31k |
| Forks | 110 | 3.0k |
| Language | TypeScript | TypeScript |
| License | Apache-2.0 | NOASSERTION |
| Last activity | 2 days ago | 2 days ago |
| Topics | memory, coding | memory, gateway |
| Curated connections | 8 | 4 |
hivemind — the curator's take
The pitch is the org-level version of agent memory: one engineer's agent figures out the tricky migration on Monday, every agent on the team executes the pattern Tuesday. Auto-learning from traces across seven agent hosts, with real LoCoMo receipts (25% cheaper, 1.7x fewer tokens vs no shared memory). Reach for it when the unit of learning is the team, not the seat. NOT local-first: cloud-backed on Deeplake is the architecture AND the business model (Activeloop, YC) — traces of your engineers' sessions leave the machine, so clear it with whoever owns your IP policy before the whole team wires in.
TencentDB-Agent-Memory — the curator's take
Use it when a team wants every agent (Claude Code, CodeBuddy, others) to share governed memory with zero integration: point the base URL at its proxy and memory is captured. Skip it if routing all LLM traffic through a proxy is unacceptable, or for a single developer: it runs three services and needs two LLM configs. Team Memory is in beta and the MongoDB backend is experimental; the license is custom.