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Octobrain

Hybrid Search • Sleep Consolidation • Knowledge Boxes

Give your AI assistant a long-term memory that outlives the context window — 22 memory types, hybrid BM25 + vector search, and a sleep-consolidation pass that folds a finished goal into one summary instead of leaving a hundred loose notes behind. Retrieval quality is a measured, reproducible BEIR benchmark, not a claim.

brew install muvon/tap/octobrain

GitHub

⭐ 14

Learn More

BEIR-Benchmarked· HyDE Query Expansion· Git-Scoped· Apache 2.0

22 Memory Types

4 MCP Tools

+2 nDCG@10 vs Bare Embedding

10-30% Recall Lift from HyDE

Key Features

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Persistent Semantic Memory

LLMs don't actually remember — they re-read every message from scratch and drop context when the window fills. Octobrain stores memories externally with vector embeddings and hybrid BM25 + vector RRF fusion, so your AI retains critical context across sessions, not just within them.

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Sleep Consolidation

Close a goal and octobrain folds every contributing memory into one archived summary — sleep-consolidate auto-clusters similar recent memories by similarity threshold, the same way biological sleep consolidates the day into fewer, stronger memories instead of a thousand loose fragments.

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Knowledge Boxes

Import a git-backed knowledge bundle — box import <repo>, scoped to one project or --global across all of them — and octobrain box sync pulls and re-indexes it. Shareable, versioned context a whole team subscribes to, not memory trapped in one machine.

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Query Expansion (HyDE-lite)

Pseudo-relevance feedback rewrites a query before search runs, lifting recall 10-30% on the long-tail queries where exact wording rarely matches how a memory was originally phrased. On by default, alongside the cross-encoder reranking stage.

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Auto-Linking & Memory Graph

Memories connect to related memories automatically via semantic similarity, or explicitly (depends_on, related_to). memory graph walks the connections multi-hop. Ebbinghaus temporal decay fades stale memories while frequently accessed ones stay strong.

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Knowledge Base Indexing

Index URLs, PDFs, and docs (.txt, .md, .pdf, .docx, .html) into chunked, searchable storage — knowledge search finds passages by meaning, knowledge match runs a regex pass, and a stale source auto-reindexes the next time it is searched.

Why Octobrain?

AI forgets everything between sessions.

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Persistent vector storage means memories survive across conversations. Context that matters is always available — not re-explained every time.

A finished project leaves behind a hundred loose, unsearchable notes.

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consolidate folds a goal's contributing memories into one archived summary; sleep-consolidate auto-clusters similar recent memories the same way.

Team knowledge lives in one person's local memory store.

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Knowledge boxes are git-backed and shareable — import once, box sync keeps every subscriber current, scoped per project or global.

"Better retrieval" is usually a claim, not a number.

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octobrain ships a reproducible BEIR benchmark against its own real retrieval path — hybrid search beats classic BM25 and the bare embedding on both measured datasets, numbers anyone can rerun.

MCP Tools

Available via Model Context Protocol for AI assistants

memorize Store a memory with metadata; related_to links it inline at creation

remember Semantic search with filters, returns 1-hop graph neighbors

forget Delete memories, with confirmation required

knowledge Unified knowledge-base tool — search, store, delete, read, match via one command field

When to Use Octobrain

Cross-Session Context

Your AI assistant remembers decisions, patterns, and preferences from previous sessions. No more repeating "we use PostgreSQL, not MySQL" every conversation.

A Finished Project Becomes One Summary

Consolidate a goal and every memory that contributed to it archives into a single record. Six weeks of debugging notes become one paragraph — searchable, not scrolled through.

Team Knowledge Shared, Not Re-Explained

Publish a knowledge box once — architecture decisions, runbooks, onboarding docs — and every teammate's AI subscribes to the same git-backed source with box sync.

Research & Documentation Recall

Index API docs, design specs, and competitor analysis. Your AI references previously read material without re-fetching — instant recall of anything it has processed.