Profile
Long-term memory layer for agents with retain/recall/reflect workflows. Integrates with Hermes via plugin or MCP and supports semantic, graph, and temporal retrieval.
Signals
Listed in the awesome-hermes-agent README
Sources: 2 / Surfaces: 1
What the upstream surface says
Short excerpt only, so you can decide whether to click out.
Documentation • Paper • Cookbook • Hindsight Cloud
[](https://github.com/vectorize-io/hindsight/actions/workflows/release.yml) [](https://join.slack.com/t/hindsight-space/shared_invite/zt-3nhbm4w29-LeSJ5Ixi6j8PdiYOCPlOgg) [](https://opensource.org/licenses/MIT) [](https://gitcgr.com/vectorize-io/hindsight)
Hindsight™ is an agent memory system built to create smarter agents that learn over time. Most agent memory systems focus on recalling conversation history. Hindsight is focused on making agents that learn, not just remember.
- World: Facts about the world ("The stove gets hot")
- Experiences: Agent's own experiences ("I touched the stove and it really hurt")
- Mental Models: Learned understanding of the agent's world formed by reflecting on raw memories and experiences.
- Retain: Provide information to Hindsight that you want it to remember
- Recall: Retrieve memories from Hindsight
- Reflect: Reflect on memories and experiences to generate new observations and insights from existing memories.
- Semantic: Vector similarity
- Keyword: BM25 exact matching