# ZeroClaw ZeroClaw is an open-source AI assistant framework built entirely in [[Rust]], designed for minimal resource consumption and maximum flexibility. Created by ZeroClaw Labs, it focuses on "zero overhead" deployment, running on hardware as cheap as a $10 [[Raspberry Pi]] while consuming less than 5MB of RAM. > Deploy anywhere, swap anything. ## How It Relates to OpenClaw ZeroClaw is a Rust-based alternative to [[OpenClaw]]. While OpenClaw is built on Node.js and focuses on messaging-app integrations and orchestration, ZeroClaw prioritizes extreme efficiency, tiny binaries, and bare-metal deployment. Both projects share the "claw" lineage and support the [[OpenClaw]] identity format, but they target different ends of the spectrum: OpenClaw for feature-rich orchestration, ZeroClaw for lean, embeddable infrastructure. ## Key Features - **Lean runtime**: Less than 5MB RAM on release builds, near-instant cold starts from a single binary - **Provider agnostic**: 29+ built-in AI model providers plus custom endpoints - **Multi-channel**: Telegram, Discord, Slack, CLI, email, and 10+ other platforms - **Trait-driven architecture**: Every subsystem (AI providers, communication channels, memory backends) can be swapped without code changes - **Security-first**: Pairing, sandboxing, explicit allowlists, and workspace scoping - **Custom memory engine**: SQLite-based vector search with FTS5 keyword indexing, no external dependencies ## Hardware Requirements - Minimum for compilation: 2GB RAM + 6GB disk - Runtime: Can operate on $10 hardware (e.g., Raspberry Pi) - Pre-built binaries available for x86_64, ARM64, and ARMv7 ## Installation ### Homebrew ```bash brew install zeroclaw ``` ### One-click Bootstrap ```bash curl -fsSL https://zeroclawlabs.ai/install.sh | bash ``` ### From Source ```bash git clone https://github.com/zeroclaw-labs/zeroclaw.git cd zeroclaw cargo build --release ``` ## Architecture ZeroClaw uses a modular trait-based architecture in Rust. Key subsystems include: - **Memory**: Custom SQLite-based vector search with FTS5 keyword indexing - **Runtime**: Native execution and Docker sandboxing - **Tools**: Shell, file operations, git, HTTP requests, scheduling, and hardware integrations - **Identity**: [[OpenClaw]] markdown and AIEOS JSON format support ## References - GitHub: https://github.com/zeroclaw-labs/zeroclaw - Website: https://zeroclawlabs.ai/ ## Related - [[OpenClaw]] - [[AI Agents]] - [[Rust]] - [[Claude Code]]