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AI 에이전트를 위한 LLM 감독형 영구 메모리로, 그래프 기반 회상, 세션 간 지식 공유, 단일 바이너리를 특징으로 합니다. DeepSeek Harness, Claude Code, OpenClaw 등 모든 에이전트 런타임과 함께 작동합니다.

Mnemon 심층 통합: 로컬 3단계 메모리(Runtime Memory, 검색 가능한 Documents, 감독형 Memory Spaces)를 제공합니다.

Cross-session memory engine for DeepSeek Harness: SQLite store + human-editable Markdown mirror, autoDream consolidation, offline semantic search (local vector/rerank/clustering), entity-attribute-timeline, Sleep Mode, custom-model autoSummarize, and 7 memory tools.

세션 간 지속성과 중요도 기반 회상을 갖춘 멀티 에이전트 시공간 메모리 그래프

Local-first persistent memory infrastructure for DeepSeek Harness: bounded hot-memory bootstrap, explainable cold recall (exact + Chinese BM25), lease-lock transactional writes, read-only governance, and trajectory review. Pure Python + Markdown, zero ext

Biomimetic memory system for DeepSeek Harness: plain-Markdown data layer, memory tools, frozen-snapshot injection, graded approval gating, structured audits, memory metabolism (dream), memory pins, semantic recall, /memory command, and cross-session retrieval.

Native StrataGate layered long-term memory for DeepSeek Harness

Automatic, local-first cross-session memory for DeepSeek Harness: layered Event/Element cards, evidence-gated recall, and expansion back to original turns and tool results.

PLUR memory rendered into the system prompt on each assembly rather than exposed as a tool call, so the block is replaced instead of appended and context stays flat across a session. Fully local hybrid search (BM25 + BGE fused with RRF), plain YAML storage you can edit, per-workspace scoping, and a /plur-memory browser.