Octobrain

Persistent memory for AI assistants with semantic search and knowledge graph relationships.

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Transport
Not stated
Package
—
Registry id
io.github.Muvon/octobrain

No install snippet on purpose. A working MCP config is a command, its arguments and an environment block — the last two are where API keys live, so this catalogue never stores them and cannot publish them. Follow the link above for the authors' own instructions.

Persistent memory for AI assistants — store insights, decisions, and knowledge that survives across conversations.

Crates.io License Rust CI Coverage

MCP Registry: mcp-name: io.github.Muvon/octobrain

Table of Contents

Octobrain gives your AI assistant a long-term memory. Store code insights, architecture decisions, bug fixes, and knowledge — then retrieve them with semantic search in future sessions. Works as a CLI tool or as an MCP server for integration with Claude Desktop and other AI tools.

Why Octobrain?

AI assistants start every conversation with zero context. You explain your project, your preferences, your decisions — every single time. Octobrain breaks that cycle:

  • Persistent memory — Insights survive across sessions, not just within them
  • Semantic search — Find memories by meaning, not exact keywords
  • Auto-linking — Related memories connect automatically (Zettelkasten-style)
  • Knowledge indexing — Ingest docs, articles, and files for retrieval
  • MCP integration — Works with Claude Desktop and other MCP-compatible tools

Quick Start

# 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

Installation

From crates.io (Recommended)

cargo install octobrain

From Source

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

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

Docker

docker pull ghcr.io/muvon/octobrain:latest

Homebrew (macOS/Linux)

brew install muvon/tap/octobrain

Feature Flags

Octobrain supports multiple embedding providers:

Flag Description API Key Required
fastembed Local embeddings via FastEmbed No
huggingface Local embeddings via HuggingFace No
(default) Both fastembed + huggingface No
(no features) API-based: Voyage, OpenAI, Google, Jina Yes
# Build with local embeddings (default, no API keys needed)
cargo build --release

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

For API-based embeddings, set the appropriate environment variable:

  • VOYAGE_API_KEY for Voyage AI
  • OPENAI_API_KEY for OpenAI
  • GOOGLE_API_KEY for Google
  • JINA_API_KEY for Jina

Usage

Memory Management

Store and retrieve insights, decisions, and context:

All memory subcommands accept global flags:

  • --scope <string> — Override project scope (default: auto-detected from Git remote)
  • --role <string> — Filter by role (e.g. "developer", "reviewer")

From the project's README.

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