Octobrain MCP server

Octobrain

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

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

Table of Contents

• Why Octobrain?
• Quick Start
• Installation
• Usage
• Features
• Benchmarks
• Configuration
• Memory Types
• MCP Integration
• Storage Locations
• Contributing
• License

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:

# 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:

• VOYAGEAPIKEY for Voyage AI
• OPENAIAPIKEY for OpenAI
• GOOGLEAPIKEY for Google
• JINAAPIKEY for Jina

Usage

Memory Management

Store and retrieve insights, decisions, and context:

All memory subcommands accept global flags:

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

Shortened. The full README is on GitHub.