Frequently Asked Questions

Yes! openclaw.ai is completely free and open-source under the MIT license. You can use it for personal, commercial, or enterprise projects without any licensing fees. However, you may incur costs from third-party API providers (like OpenAI or Anthropic) if you choose to use their services.

Minimum requirements:

• 2GB RAM (4GB recommended)
• 2GB free disk space
• Node.js 22 or higher
• 64-bit operating system
• Internet connection (for cloud LLM APIs)

Recommended for production:

• 4GB+ RAM
• 10GB+ disk space
• Multi-core CPU
• SSD storage

openclaw.ai runs on all major operating systems:

• Windows: Windows 10/11 (64-bit)
• macOS: macOS 11+ (Intel and Apple Silicon)
• Linux: Ubuntu 20.04+, Debian 11+, Fedora 38+, Arch, and most other distributions
• Containers: Docker, Kubernetes
• Special Hardware: Raspberry Pi 4/5

Installation time varies by platform and experience level:

• Docker: 5-15 minutes (fastest)
• Linux/macOS: 15-20 minutes
• Windows: 20-30 minutes
• Cloud VPS: 25-45 minutes
• Raspberry Pi: 45-60 minutes
• Kubernetes: 60-90 minutes

Our beginner tutorials require no prior programming experience. You'll be copying and pasting commands with clear explanations of what each step does. However, for advanced tutorials (production deployment, Kubernetes), basic familiarity with command-line interfaces and server administration is helpful.

Yes! You can install openclaw.ai using the install script which handles permissions automatically. Alternatively, you can configure npm to install global packages in your home directory. However, some features (like running the daemon on startup) may require administrator privileges.

openclaw.ai supports a wide range of LLM providers:

• Cloud APIs: OpenAI, Anthropic, Google, Mistral, Cohere
• Local LLMs: Ollama, LM Studio, llama.cpp, vLLM
• Self-hosted: HuggingFace TGI, OpenRouter

You can even use multiple providers simultaneously and switch between them based on task requirements.

Yes! You can run openclaw.ai completely offline by using local LLMs such as:

• Ollama: Easy setup, runs many open-source models
• LM Studio: GUI-based, great for beginners
• llama.cpp: Lightweight, runs on minimal hardware

This allows fully private operation without sending any data to external services.

Updating is simple:

npm install -g openclaw@latest

For Docker users:

docker pull openclaw/openclaw:latest
docker-compose up -d

This usually means Node.js isn't installed or the npm global bin isn't in your system PATH. Solutions:

1. Install Node.js 22+ from nodejs.org
2. Check your version: node --version (must be 22 or higher)
3. If openclaw is not found, add npm global bin to PATH: export PATH="$(npm prefix -g)/bin:$PATH"

Try these solutions:

• Use the install script instead: curl -fsSL https://openclaw.ai/install.sh | bash
• Check your internet connection
• Temporarily disable antivirus/firewall
• If using VPN, try disconnecting

Don't use sudo npm install -g! Instead:

1. Fix npm permissions: mkdir ~/.npm-global && npm config set prefix '~/.npm-global'
2. Or use the install script: curl -fsSL https://openclaw.ai/install.sh | bash

To completely remove openclaw.ai:

# Uninstall the package
npm uninstall -g openclaw

# Remove configuration files
rm -rf ~/.openclaw

# For Docker
docker rm -f openclaw
docker rmi openclaw/openclaw