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OpenClaw supports onboarding from the terminal, the macOS app, and the Linux desktop companion. Every path establishes inference first: it detects existing AI access, requires a live completion, and only then starts OpenClaw to configure the remaining setup. Desktop apps verify an already configured model before opening the normal agent UI instead of repeating guided onboarding. The terminal flow also offers the full classic wizard for detailed setup.

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Which path should I use?

Most users should start with CLI onboarding — it works everywhere and gives you the most control.

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What onboarding configures

The guided inference phase establishes only:
  1. Model provider and auth — detected access or a verified provider sign-in, API key, or token
  2. Verified inference — a real completion on the default agent’s effective model
After that completion passes, OpenClaw can configure the workspace, Gateway, Gateway service, channels, agents, plugins, and other optional features. The classic CLI wizard can additionally configure:
  1. Channels (optional) — built-in and bundled chat channels such as Discord, Feishu, Google Chat, iMessage, Mattermost, Microsoft Teams, Telegram, WhatsApp, and more
  2. Advanced Gateway controls — remote mode, network settings, and daemon choices

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CLI onboarding

Run in any terminal:
The guided flow detects existing AI access, live-tests candidates in order, and falls through on failure. If detection is exhausted, it shows OpenAI, Anthropic, xAI (Grok), Google, and OpenRouter first. More… contains the remaining providers in provider groups, with regions, plans, and supported browser, device, API-key, or token methods in a second menu. It saves the model and credential only after a passing completion, then starts OpenClaw to configure the workspace, Gateway, channels, agents, plugins, and other optional features. Skip for now exits without starting OpenClaw. There is no in-flow classic handoff; exit and run openclaw onboard --classic when you want the classic wizard instead. After inference passes, OpenClaw can hand channel setup to a masked terminal wizard. It does not open guided or classic provider setup; exit OpenClaw and run openclaw onboard to change the model provider or its authentication. Use openclaw onboard --classic for detailed model/auth, channel, skill, remote Gateway, or import setup. Adding --install-daemon also selects the classic flow and installs the background service in one step. Use openclaw setup for conversational non-inference setup and repair. openclaw onboard --modern is a compatibility alias that uses the same live-inference gate. Full reference: Onboarding (CLI) CLI command docs: openclaw onboard

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macOS app onboarding

Download the macOS app, then open it. If its configured local or remote Gateway is reachable and the default agent already has a configured model, the app verifies that model with a real reply before opening the normal dashboard. For a fresh or incomplete Gateway, native setup handles the Gateway connection, any needed local CLI/runtime install, and AI access. It detects existing credentials or eligible loaded local models, live-tests candidates, and offers provider sign-in or masked key/token entry when needed. After a new model passes, the app opens guided onboarding in the dashboard for optional setup, including memory import and channels, before the handoff to normal agent chat. Memory import and permissions are not separate native first-run pages; macOS permissions remain available in Settings → Permissions. Gemini CLI remains available as an explicitly configured runtime after setup, but Gemini CLI and Antigravity are not offered as detected inference routes. Use Google AI Studio API-key or Vertex AI for guided setup. The optional Gemini CLI runtime specifically requires an AI Studio API-key profile. Full reference: Onboarding (macOS App)

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Linux app onboarding

Install the Linux desktop companion, then open it. The welcome screen lets you choose a Gateway on this computer or another computer. Local setup installs any missing CLI and Node in a private managed runtime, then starts the systemd user service. Remote setup connects to a discovered Gateway, a manually entered Gateway URL, or a Gateway reached through an SSH tunnel; token and password authentication are supported. Model Setup checks existing provider access and offers sign-in or API-key entry when needed. The selected Gateway verifies a real model response before guided onboarding begins. An already configured Gateway opens the normal agent UI after verification instead. Restart/reopen recovery uses a temporary record bound to the Gateway, agent, and authentication: a known model is verified without repeating activation, while an unknown result needs the explicit Verify & use selected model action. Expiry, cleared or unavailable browser storage, or changed connection ownership can prevent recovery. See First-run setup for recovery details. Platform and remote-access details: Linux app and Remote access.

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Custom or unlisted providers

If your provider is not listed, run openclaw onboard in a terminal on the Gateway host, choose Custom Provider (under More… when shown), and enter:
  • Endpoint compatibility: OpenAI-compatible (/chat/completions), OpenAI Responses-compatible (/responses), Anthropic-compatible (/messages), or unknown (probes all three and auto-detects)
  • Base URL and API key (API key is optional if the endpoint does not require one)
  • Model ID and optional model alias
Multiple custom endpoints can coexist — each gets its own endpoint ID. Guided setup verifies a real model reply before saving the provider and activating its model. A failed or cancelled check preserves the previous configuration. The classic wizard also retains its custom-provider setup.