kevin-hs-sohn/hipocampus
159 stars · Last commit 2026-04-24
Drop-in memory harness for AI agents — 3-tier memory, compaction tree, hybrid search. One command to set up. Works with Claude Code and OpenClaw.
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# hipocampus Drop-in **proactive memory** harness for AI agents. Zero infrastructure — just files. One command to set up. Works immediately with [Claude Code](https://claude.ai/code), [OpenCode](https://opencode.ai/), and [OpenClaw](https://github.com/openclaw). ## Benchmark Evaluated on [MemAware](https://github.com/kevin-hs-sohn/memaware) — 900 implicit context questions across 3 months of conversation history. The agent must proactively surface relevant past context that the user never explicitly asks about. | Method | Easy (n=300) | Medium (n=300) | Hard (n=300) | **Overall** | |--------|:---:|:---:|:---:|:---:| | No Memory | 1.0% | 0.7% | 0.7% | 0.8% | | BM25 Search | 4.7% | 1.7% | 2.0% | 2.8% | | BM25 + Vector Search | 6.0% | 3.7% | 0.7% | 3.4% | | **Hipocampus (tree only)** | **14.7%** | **5.7%** | **7.3%** | **9.2%** | | **Hipocampus + BM25** | **18.7%** | **10.0%** | **5.7%** | **11.4%** | | **Hipocampus + Vector** | **26.0%** | **18.0%** | **8.0%** | **17.3%** | | **Hipocampus + Vector (10K ROOT)** | **34.0%** | **21.0%** | **8.0%** | **21.0%** |