How to Self-Host OpenClaw: A Complete Deployment Guide

Introduction to OpenClaw

OpenClaw (formerly known as Clawdbot or Moltbot) has rapidly become one of the fastest-growing open-source projects in GitHub history, amassing over 100,000 stars in just a few days. It is a powerful, self-hosted AI personal assistant platform designed to operate 24/7. Unlike standard web-based AI chatbots, OpenClaw functions as an autonomous agent capable of executing system commands, managing files, controlling browsers, and integrating with multiple messaging platforms like Telegram, WhatsApp, Slack, and Discord.

By self-hosting OpenClaw, users gain complete control over their data privacy while enjoying enterprise-level automation capabilities. This guide provides a comprehensive, step-by-step walkthrough on how to deploy OpenClaw on a local machine or a cloud server.

Core Architecture and Features

Understanding the underlying mechanics of OpenClaw is crucial for a successful deployment. The system operates on a Gateway WebSocket architecture, routing inbound messages into isolated agent sessions. Key features include:

• Persistent Memory: Maintains context across sessions and platforms using a hybrid vector search and a dynamically updated MEMORY.md file.
• Multi-Model Support: Integrates seamlessly with cloud providers (Anthropic Claude, OpenAI GPT, Google Gemini) and local models via Ollama.
• System Automation: Capable of executing shell commands, reading/writing files, and performing browser automation via semantic snapshots instead of heavy image processing.
• Omnichannel Gateway: A single AI agent can manage communications across more than ten different instant messaging platforms simultaneously.

System Requirements

Before initiating the installation process, ensure the host environment meets the necessary hardware and software prerequisites.

Step-by-Step Deployment Guide

Step 1: Environment Preparation (Installing Node.js)

OpenClaw is built on TypeScript and requires a modern Node.js runtime. It is highly recommended to use Node Version Manager (NVM) to prevent permission issues and allow easy version switching.

# Install NVM (Node Version Manager)
curl -o- https://raw.githubusercontent.com/nvm-sh/nvm/v0.39.7/install.sh | bash

# Reload shell configuration
source ~/.bashrc  # or ~/.zshrc for macOS

# Install and use Node.js version 24
nvm install 24
nvm use 24

Verify the installation by running node --version. The output should indicate a version of 22.0 or higher.

Step 2: Running the Installation Script

The OpenClaw development team provides streamlined installation scripts for different operating systems. These scripts automatically detect the environment, check dependencies, and install the core application.

For macOS and Linux:

curl -fsSL https://openclaw.ai/install.sh | bash

For Windows (via PowerShell):

iwr -useb https://openclaw.ai/install.ps1 | iex

Alternatively, OpenClaw can be installed globally via NPM:

npm install -g openclaw@latest

Step 3: Initialization and Gateway Setup

Once the installation completes, the initialization wizard must be executed to configure the daemon, set up the gateway port, and define the default AI model.

openclaw onboard --install-daemon

Follow the interactive prompts. The setup will configure the local WebSocket control panel (typically running on ws://127.0.0.1:18789). To verify the service status, execute:

openclaw status
openclaw health

Configuring AI Models

OpenClaw’s flexibility allows it to run entirely offline using local hardware or leverage powerful cloud-based APIs.

Option A: Using Local Models via Ollama (Free & Private)

For maximum privacy, running local models is the best approach. Ollama makes it effortless to run large language models locally.

1. Install Ollama from the official website or via Homebrew (brew install ollama).
2. Download a suitable model. For machines with 8GB-16GB RAM, qwen2.5:7b or llama3:8b is recommended:

   ollama run qwen2.5:7b

3. In the OpenClaw configuration menu, select Custom Provider and input the local Ollama endpoint (usually http://127.0.0.1:11434/v1).

Option B: Using Cloud Providers (GitHub Copilot / Qwen)

If hardware resources are limited, utilizing cloud APIs is highly efficient. OpenClaw provides native authentication for several providers.

Authenticating with GitHub Copilot:

openclaw models auth login-github-copilot
openclaw models set github-copilot/claude-opus-4.5

Authenticating with Qwen (Free Tier):

openclaw plugins enable qwen-portal-auth
openclaw gateway restart
openclaw models auth login --provider qwen-portal --set-default

Video Tutorial: OpenClaw Setup

For a visual walkthrough of the installation process, refer to the following demonstration:

OpenClaw vs. Traditional SaaS AI Assistants

Why choose a self-hosted solution over commercial SaaS products? The following comparison highlights the strategic advantages:

Conclusion

Deploying OpenClaw transforms a standard computer into a highly capable, autonomous AI workstation. By following this guide, users can successfully configure the environment, connect preferred language models, and integrate the assistant into daily workflows. For further advanced configurations, refer to the official OpenClaw GitHub repository.