Octobrain

# Install from crates.io
cargo install octobrain

# Store your first memory
octobrain memory memorize --title "API Design Pattern" \
  --content "Use REST for CRUD, GraphQL for complex queries" \
  --memory-type architecture --tags "api,design"

# Search memories
octobrain memory remember "how should I design APIs"

# Start MCP server for Claude Desktop integration
octobrain mcp

cargo install octobrain

# Clone and build
git clone https://github.com/muvon/octobrain.git
cd octobrain
cargo build --release

# Binary location
./target/release/octobrain --help

docker pull ghcr.io/muvon/octobrain:latest

brew install muvon/tap/octobrain

# Build with local embeddings (default, no API keys needed)
cargo build --release

# Build with API-based embeddings only
cargo build --no-default-features --release

# Store a memory
octobrain memory memorize --title "API Design" \
  --content "Use REST for CRUD, GraphQL for complex queries" \
  --memory-type architecture --tags "api,design"

# Search memories (semantic search)
octobrain memory remember "api design patterns"

# Multi-query search for broader coverage
octobrain memory remember "authentication" "security" "jwt"

# Get a memory by ID
octobrain memory get <id>

# Get recent memories
octobrain memory recent --limit 20

# Filter by type
octobrain memory by-type architecture --limit 10

# Filter by tags
octobrain memory by-tags "api,security"

# Find memories related to files
octobrain memory for-files "src/main.rs,src/lib.rs"

# Update a memory
octobrain memory update <id> --title "New Title" --add-tags "new-tag"

# Delete a memory
octobrain memory forget --memory-id <id>

# Get memories relevant to the current Git commit
octobrain memory current-commit

# Show memory statistics
octobrain memory stats

# Clean up old/low-importance memories
octobrain memory cleanup

# Compact tables and refresh indices (run when searches slow down)
octobrain memory maintenance

# ⚠️ Delete ALL memory data
octobrain memory clear-all --yes

# Consolidate a goal (Achieves-link sources → Consolidated state, importance dampened)
octobrain memory consolidate <goal-id> --summary "Final summary"

# Sleep consolidation: auto-cluster recent similar memories
octobrain memory sleep-consolidate --threshold 0.85 --min-size 3

# Create a relationship between memories
octobrain memory relate <source-id> <target-id> \
  --relationship-type "depends_on" \
  --description "Source requires target to function"

# View relationships for a memory
octobrain memory relationships <memory-id>

# Find related memories through relationships
octobrain memory related <memory-id>

# Auto-link similar memories (Zettelkasten-style)
octobrain memory auto-link <memory-id>

# Explore memory graph
octobrain memory graph <memory-id> --depth 2

# Index a URL
octobrain knowledge index https://docs.rs/tokio/latest/tokio/

# Index a local file (.txt, .md, .pdf, .docx, .html)
octobrain knowledge index ./docs/architecture.md

# Search knowledge base
octobrain knowledge search "how to handle async tasks"

# Search within a specific source (auto-indexes if outdated)
octobrain knowledge search "spawn blocking" --source https://docs.rs/tokio/

# Read full content of a URL or local file
octobrain knowledge read https://docs.rs/tokio/latest/tokio/

# Search indexed content by regex pattern
octobrain knowledge match "spawn_blocking|block_in_place"

# Store raw text content
octobrain knowledge store "meeting-notes" --content "Discussion points..."

# List indexed sources
octobrain knowledge list --limit 20

# Show statistics
octobrain knowledge stats

# Delete a source
octobrain knowledge delete https://example.com/docs

# Delete stored content by key
octobrain knowledge delete-stored "meeting-notes"

# Import a remote git repo as a knowledge box
octobrain box import https://github.com/org/docs-repo.git

# Import at global scope (visible in every project)
octobrain box import https://github.com/org/docs-repo.git --global

# Pull and re-index all subscribed boxes + local .box/ directories
# (the MCP server syncs each session's repos on first contact; agents run `knowledge` `sync` after editing .box/)
octobrain box sync

# List subscribed boxes
octobrain box list

# Remove a box
octobrain box remove github.com/org/docs-repo

# Start with stdio transport (for Claude Desktop)
octobrain mcp

# Start with HTTP transport (for web-based tools)
octobrain mcp --bind 0.0.0.0:12345

cd benches && bash scripts/run_retrieval.sh

[embedding]
# Local models (no API key, runs on CPU, model auto-downloaded on first use)
model = "fastembed:Qdrant/all-MiniLM-L6-v2-onnx"                       # Default: 384-dim quantized, ~125MB resident
model = "fastembed:nomic-ai/nomic-embed-text-v1.5"                      # 768-dim, 8192-ctx, ~550MB weights, highest quality
model = "fastembed:BAAI/bge-small-en-v1.5"                              # 384-dim, ~62 MTEB, fast + good quality
model = "fastembed:sentence-transformers/all-MiniLM-L6-v2-quantized"  # Smallest (~22MB), fastest
model = "fastembed:BAAI/bge-base-en-v1.5"                              # Larger (~440MB), higher quality
model = "fastembed:intfloat/multilingual-e5-small"                     # Multilingual

# Cloud providers (require API keys, generally higher quality)
model = "voyage:voyage-3.5-lite"          # VOYAGE_API_KEY
model = "openai:text-embedding-3-small"   # OPENAI_API_KEY
model = "google:text-embedding-004"       # GOOGLE_API_KEY
model = "jina:jina-embeddings-v3"         # JINA_API_KEY

{
  "mcpServers": {
    "octobrain": {
      "command": "/path/to/octobrain",
      "args": ["mcp"]
    }
  }
}

octobrain mcp --bind 0.0.0.0:12345

# Clone and build
git clone https://github.com/muvon/octobrain.git
cd octobrain
cargo build --no-default-features

# Run tests
cargo test --no-default-features

# Run clippy
cargo clippy --no-default-features