Quick answers plus deeper troubleshooting for real-world setups (local dev, VPS, multi-agent, OAuth/API keys, model failover). For runtime diagnostics, see Troubleshooting. For the full config reference, see Configuration.
Use a local AI agent that can see your machine. That is far more effective than asking
in Discord, because most “I’m stuck” cases are local config or environment issues that
remote helpers cannot inspect.
These tools can read the repo, run commands, inspect logs, and help fix your machine-level
setup (PATH, services, permissions, auth files). Give them the full source checkout via
the hackable (git) install:
This installs OpenClaw from a git checkout, so the agent can read the code + docs and
reason about the exact version you are running. You can always switch back to stable later
by re-running the installer without --install-method git.
Tip: ask the agent to plan and supervise the fix (step-by-step), then execute only the
necessary commands. That keeps changes small and easier to audit.
The repo recommends running from source and using onboarding:
Terminal window
curl-fsSLhttps://openclaw.ai/install.sh|bash
openclawonboard--install-daemon
The wizard can also build UI assets automatically. After onboarding, you typically run the Gateway on port 18789.
From source (contributors/dev):
Terminal window
gitclonehttps://github.com/openclaw/openclaw.git
cdopenclaw
pnpminstall
pnpmbuild
pnpmui:build# auto-installs UI deps on first run
openclawonboard
If you don’t have a global install yet, run it via pnpm openclaw onboard.
How do I open the dashboard after onboarding?
The wizard opens your browser with a clean (non-tokenized) dashboard URL right after onboarding and also prints the link in the summary. Keep that tab open; if it didn’t launch, copy/paste the printed URL on the same machine.
How do I authenticate the dashboard (token) on localhost vs remote?
Localhost (same machine):
Open http://127.0.0.1:18789/.
If it asks for auth, paste the token from gateway.auth.token (or OPENCLAW_GATEWAY_TOKEN) into Control UI settings.
Retrieve it from the gateway host: openclaw config get gateway.auth.token (or generate one: openclaw doctor --generate-gateway-token).
Not on localhost:
Tailscale Serve (recommended): keep bind loopback, run openclaw gateway --tailscale serve, open `https://
/. If gateway.auth.allowTailscaleistrue, identity headers satisfy Control UI/WebSocket auth (no token, assumes trusted gateway host); HTTP APIs still require token/password. - **Tailnet bind**: run openclaw gateway —bind tailnet —token ”
“, open http://
:18789/, paste token in dashboard settings. - **SSH tunnel**: ssh -N -L 18789:127.0.0.1:18789 user@hostthen openhttp://127.0.0.1:18789/` and paste the token in Control UI settings.
See [Dashboard](/en/web/dashboard) and [Web surfaces](/en/web) for bind modes and auth details.
Why are there two exec approval configs for chat approvals?
They control different layers:
approvals.exec: forwards approval prompts to chat destinations
`channels.
.execApprovals`: makes that channel act as a native approval client
The host exec policy is still the real approval gate. Chat config only controls where approval
prompts appear and how people can answer them.
In most setups you do **not** need both:
- If the chat already supports commands and replies, same-chat `/approve` works through the shared path.
- If a supported native channel can infer approvers safely, OpenClaw now auto-enables DM-first native approvals when `channels.
.execApprovals.enabledis unset or”auto”. - Use approvals.execonly when prompts must also be forwarded to other chats or explicit ops rooms. - Usechannels.
.execApprovals.target: “channel”or”both”` only when you explicitly want approval prompts posted back into the originating room/topic.
Short version: forwarding is for routing, native client config is for richer channel-specific UX.
See [Exec Approvals](/en/tools/exec-approvals).
What runtime do I need?
Node >= 22 is required. pnpm is recommended. Bun is not recommended for the Gateway.
Does it run on Raspberry Pi?
Yes. The Gateway is lightweight - docs list 512MB-1GB RAM, 1 core, and about 500MB
disk as enough for personal use, and note that a Raspberry Pi 4 can run it.
If you want extra headroom (logs, media, other services), 2GB is recommended, but it’s
not a hard minimum.
Tip: a small Pi/VPS can host the Gateway, and you can pair nodes on your laptop/phone for
local screen/camera/canvas or command execution. See Nodes.
Any tips for Raspberry Pi installs?
Short version: it works, but expect rough edges.
Use a 64-bit OS and keep Node >= 22.
Prefer the hackable (git) install so you can see logs and update fast.
Start without channels/skills, then add them one by one.
If you hit weird binary issues, it is usually an ARM compatibility problem.
It is stuck on wake up my friend / onboarding will not hatch. What now?
That screen depends on the Gateway being reachable and authenticated. The TUI also sends
“Wake up, my friend!” automatically on first hatch. If you see that line with no reply
and tokens stay at 0, the agent never ran.
Restart the Gateway:
Terminal window
openclawgatewayrestart
Check status + auth:
Terminal window
openclawstatus
openclawmodelsstatus
openclawlogs--follow
If it still hangs, run:
Terminal window
openclawdoctor
If the Gateway is remote, ensure the tunnel/Tailscale connection is up and that the UI
is pointed at the right Gateway. See Remote access.
Can I migrate my setup to a new machine (Mac mini) without redoing onboarding?
Yes. Copy the state directory and workspace, then run Doctor once. This
keeps your bot “exactly the same” (memory, session history, auth, and channel
state) as long as you copy both locations:
Install OpenClaw on the new machine.
Copy $OPENCLAW_STATE_DIR (default: ~/.openclaw) from the old machine.
Copy your workspace (default: ~/.openclaw/workspace).
Run openclaw doctor and restart the Gateway service.
That preserves config, auth profiles, WhatsApp creds, sessions, and memory. If you’re in
remote mode, remember the gateway host owns the session store and workspace.
Important: if you only commit/push your workspace to GitHub, you’re backing
up memory + bootstrap files, but not session history or auth. Those live
under ~/.openclaw/ (for example `~/.openclaw/agents/
/sessions/`).
Related: [Migrating](/en/install/migrating), [Where things live on disk](#where-things-live-on-disk),
Newest entries are at the top. If the top section is marked Unreleased, the next dated
section is the latest shipped version. Entries are grouped by Highlights, Changes, and
Fixes (plus docs/other sections when needed).
Cannot access docs.openclaw.ai (SSL error)
Some Comcast/Xfinity connections incorrectly block docs.openclaw.ai via Xfinity
Advanced Security. Disable it or allowlist docs.openclaw.ai, then retry.
Please help us unblock it by reporting here: https://spa.xfinity.com/check_url_status.
Stable and beta are npm dist-tags, not separate code lines:
latest = stable
beta = early build for testing
Usually, a stable release lands on beta first, then an explicit
promotion step moves that same version to latest. Maintainers can also
publish straight to latest when needed. That’s why beta and stable can
point at the same version after promotion.
The docs did not answer my question - how do I get a better answer?
Use the hackable (git) install so you have the full source and docs locally, then ask
your bot (or Claude/Codex) from that folder so it can read the repo and answer precisely.
How it works in the cloud: the Gateway runs on the server, and you access it
from your laptop/phone via the Control UI (or Tailscale/SSH). Your state + workspace
live on the server, so treat the host as the source of truth and back it up.
You can pair nodes (Mac/iOS/Android/headless) to that cloud Gateway to access
local screen/camera/canvas or run commands on your laptop while keeping the
Gateway in the cloud.
Short answer: possible, not recommended. The update flow can restart the
Gateway (which drops the active session), may need a clean git checkout, and
can prompt for confirmation. Safer: run updates from a shell as the operator.
Daemon install (LaunchAgent on macOS; systemd user unit on Linux/WSL2)
Health checks and skills selection
It also warns if your configured model is unknown or missing auth.
Do I need a Claude or OpenAI subscription to run this?
No. You can run OpenClaw with API keys (Anthropic/OpenAI/others) or with
local-only models so your data stays on your device. Subscriptions (Claude
Pro/Max or OpenAI Codex) are optional ways to authenticate those providers.
If you choose Anthropic subscription auth, decide for yourself whether to use it:
Anthropic has blocked some subscription usage outside Claude Code in the past.
OpenAI Codex OAuth is explicitly supported for external tools like OpenClaw.
Can I use Claude Max subscription without an API key?
Yes. You can either use a setup-token or reuse a local Claude CLI
login on the gateway host.
Claude Pro/Max subscriptions do not include an API key, so this is the
technical path for subscription accounts. But this is your decision: Anthropic
has blocked some subscription usage outside Claude Code in the past.
If you want the clearest and safest supported path for production, use an Anthropic API key.
How does Anthropic setup-token auth work?
claude setup-token generates a token string via the Claude Code CLI (it is not available in the web console). You can run it on any machine. Choose Anthropic token (paste setup-token) in onboarding or paste it with openclaw models auth paste-token --provider anthropic. The token is stored as an auth profile for the anthropic provider and used like an API key (no auto-refresh). More detail: OAuth.
Where do I find an Anthropic setup-token?
It is not in the Anthropic Console. The setup-token is generated by the Claude Code CLI on any machine:
Terminal window
claudesetup-token
Copy the token it prints, then choose Anthropic token (paste setup-token) in onboarding. If you want to run it on the gateway host, use openclaw models auth setup-token --provider anthropic. If you ran claude setup-token elsewhere, paste it on the gateway host with openclaw models auth paste-token --provider anthropic. See Anthropic.
Do you support Claude subscription auth (Claude Pro or Max)?
Yes. You can either:
use a setup-token
reuse a local Claude CLI login on the gateway host with openclaw models auth login --provider anthropic --method cli --set-default
Setup-token is still supported. Claude CLI migration is simpler when the gateway host already runs Claude Code. See Anthropic and OAuth.
Important: this is technical compatibility, not a policy guarantee. Anthropic
has blocked some subscription usage outside Claude Code in the past.
You need to decide whether to use it and verify Anthropic’s current terms.
For production or multi-user workloads, Anthropic API key auth is the safer, recommended choice.
Why am I seeing HTTP 429 rate_limit_error from Anthropic?
That means your Anthropic quota/rate limit is exhausted for the current window. If you
use a Claude subscription (setup-token), wait for the window to
reset or upgrade your plan. If you use an Anthropic API key, check the Anthropic Console
for usage/billing and raise limits as needed.
If the message is specifically:
`Extra usage is required for long context requests`, the request is trying to use
Anthropic's 1M context beta (`context1m: true`). That only works when your
credential is eligible for long-context billing (API key billing or subscription
with Extra Usage enabled).
Tip: set a **fallback model** so OpenClaw can keep replying while a provider is rate-limited.
See [Models](/en/cli/models), [OAuth](/en/concepts/oauth), and
Yes - via pi-ai’s Amazon Bedrock (Converse) provider with manual config. You must supply AWS credentials/region on the gateway host and add a Bedrock provider entry in your models config. See Amazon Bedrock and Model providers. If you prefer a managed key flow, an OpenAI-compatible proxy in front of Bedrock is still a valid option.
How does Codex auth work?
OpenClaw supports OpenAI Code (Codex) via OAuth (ChatGPT sign-in). Onboarding can run the OAuth flow and will set the default model to openai-codex/gpt-5.4 when appropriate. See Model providers and Onboarding (CLI).
Do you support OpenAI subscription auth (Codex OAuth)?
Yes. OpenClaw fully supports OpenAI Code (Codex) subscription OAuth.
OpenAI explicitly allows subscription OAuth usage in external tools/workflows
like OpenClaw. Onboarding can run the OAuth flow for you.
This stores OAuth tokens in auth profiles on the gateway host. Details: Model providers.
Is a local model OK for casual chats?
Usually no. OpenClaw needs large context + strong safety; small cards truncate and leak. If you must, run the largest model build you can locally (LM Studio) and see /gateway/local-models. Smaller/quantized models increase prompt-injection risk - see Security.
How do I keep hosted model traffic in a specific region?
Pick region-pinned endpoints. OpenRouter exposes US-hosted options for MiniMax, Kimi, and GLM; choose the US-hosted variant to keep data in-region. You can still list Anthropic/OpenAI alongside these by using models.mode: "merge" so fallbacks stay available while respecting the regioned provider you select.
Do I have to buy a Mac Mini to install this?
No. OpenClaw runs on macOS or Linux (Windows via WSL2). A Mac mini is optional - some people
buy one as an always-on host, but a small VPS, home server, or Raspberry Pi-class box works too.
You only need a Mac for macOS-only tools. For iMessage, use BlueBubbles (recommended) - the BlueBubbles server runs on any Mac, and the Gateway can run on Linux or elsewhere. If you want other macOS-only tools, run the Gateway on a Mac or pair a macOS node.
You need some macOS device signed into Messages. It does not have to be a Mac mini -
any Mac works. Use BlueBubbles (recommended) for iMessage - the BlueBubbles server runs on macOS, while the Gateway can run on Linux or elsewhere.
Common setups:
Run the Gateway on Linux/VPS, and run the BlueBubbles server on any Mac signed into Messages.
Run everything on the Mac if you want the simplest single-machine setup.
If I buy a Mac mini to run OpenClaw, can I connect it to my MacBook Pro?
Yes. The Mac mini can run the Gateway, and your MacBook Pro can connect as a
node (companion device). Nodes don’t run the Gateway - they provide extra
capabilities like screen/camera/canvas and system.run on that device.
Common pattern:
Gateway on the Mac mini (always-on).
MacBook Pro runs the macOS app or a node host and pairs to the Gateway.
Use openclaw nodes status / openclaw nodes list to see it.
See [/channels/telegram](/en/channels/telegram#access-control-and-activation).
Can multiple people use one WhatsApp number with different OpenClaw instances?
Yes, via multi-agent routing. Bind each sender’s WhatsApp DM (peer kind: "direct", sender E.164 like +15551234567) to a different agentId, so each person gets their own workspace and session store. Replies still come from the same WhatsApp account, and DM access control (channels.whatsapp.dmPolicy / channels.whatsapp.allowFrom) is global per WhatsApp account. See Multi-Agent Routing and WhatsApp.
Can I run a "fast chat" agent and an "Opus for coding" agent?
Yes. Use multi-agent routing: give each agent its own default model, then bind inbound routes (provider account or specific peers) to each agent. Example config lives in Multi-Agent Routing. See also Models and Configuration.
Does Homebrew work on Linux?
Yes. Homebrew supports Linux (Linuxbrew). Quick setup:
If you run OpenClaw via systemd, ensure the service PATH includes `/home/linuxbrew/.linuxbrew/bin` (or your brew prefix) so `brew`-installed tools resolve in non-login shells.
Recent builds also prepend common user bin dirs on Linux systemd services (for example `~/.local/bin`, `~/.npm-global/bin`, `~/.local/share/pnpm`, `~/.bun/bin`) and honor `PNPM_HOME`, `NPM_CONFIG_PREFIX`, `BUN_INSTALL`, `VOLTA_HOME`, `ASDF_DATA_DIR`, `NVM_DIR`, and `FNM_DIR` when set.
Difference between the hackable git install and npm install
Hackable (git) install: full source checkout, editable, best for contributors.
You run builds locally and can patch code/docs.
npm install: global CLI install, no repo, best for “just run it.”
Updates come from npm dist-tags.
Yes. Install the other flavor, then run Doctor so the gateway service points at the new entrypoint.
This does not delete your data - it only changes the OpenClaw code install. Your state
(~/.openclaw) and workspace (~/.openclaw/workspace) stay untouched.
From npm to git:
Terminal window
gitclonehttps://github.com/openclaw/openclaw.git
cdopenclaw
pnpminstall
pnpmbuild
openclawdoctor
openclawgatewayrestart
From git to npm:
Terminal window
npminstall-gopenclaw@latest
openclawdoctor
openclawgatewayrestart
Doctor detects a gateway service entrypoint mismatch and offers to rewrite the service config to match the current install (use --repair in automation).
Short answer: if you want 24/7 reliability, use a VPS. If you want the
lowest friction and you’re okay with sleep/restarts, run it locally.
Laptop (local Gateway)
Pros: no server cost, direct access to local files, live browser window.
Cons: sleep/network drops = disconnects, OS updates/reboots interrupt, must stay awake.
VPS / cloud
Pros: always-on, stable network, no laptop sleep issues, easier to keep running.
Cons: often run headless (use screenshots), remote file access only, you must SSH for updates.
OpenClaw-specific note: WhatsApp/Telegram/Slack/Mattermost (plugin)/Discord all work fine from a VPS. The only real trade-off is headless browser vs a visible window. See Browser.
Recommended default: VPS if you had gateway disconnects before. Local is great when you’re actively using the Mac and want local file access or UI automation with a visible browser.
How important is it to run OpenClaw on a dedicated machine?
Not required, but recommended for reliability and isolation.
Shared laptop/desktop: totally fine for testing and active use, but expect pauses when the machine sleeps or updates.
If you want the best of both worlds, keep the Gateway on a dedicated host and pair your laptop as a node for local screen/camera/exec tools. See Nodes.
For security guidance, read Security.
What are the minimum VPS requirements and recommended OS?
OpenClaw is lightweight. For a basic Gateway + one chat channel:
Absolute minimum: 1 vCPU, 1GB RAM, ~500MB disk.
Recommended: 1-2 vCPU, 2GB RAM or more for headroom (logs, media, multiple channels). Node tools and browser automation can be resource hungry.
OS: use Ubuntu LTS (or any modern Debian/Ubuntu). The Linux install path is best tested there.
Can I run OpenClaw in a VM and what are the requirements?
Yes. Treat a VM the same as a VPS: it needs to be always on, reachable, and have enough
RAM for the Gateway and any channels you enable.
Baseline guidance:
Absolute minimum: 1 vCPU, 1GB RAM.
Recommended: 2GB RAM or more if you run multiple channels, browser automation, or media tools.
OS: Ubuntu LTS or another modern Debian/Ubuntu.
If you are on Windows, WSL2 is the easiest VM style setup and has the best tooling
compatibility. See Windows, VPS hosting.
If you are running macOS in a VM, see macOS VM.
OpenClaw is a personal AI assistant you run on your own devices. It replies on the messaging surfaces you already use (WhatsApp, Telegram, Slack, Mattermost (plugin), Discord, Google Chat, Signal, iMessage, WebChat) and can also do voice + a live Canvas on supported platforms. The Gateway is the always-on control plane; the assistant is the product.
Value proposition
OpenClaw is not “just a Claude wrapper.” It’s a local-first control plane that lets you run a
capable assistant on your own hardware, reachable from the chat apps you already use, with
stateful sessions, memory, and tools - without handing control of your workflows to a hosted
SaaS.
Highlights:
Your devices, your data: run the Gateway wherever you want (Mac, Linux, VPS) and keep the
workspace + session history local.
Real channels, not a web sandbox: WhatsApp/Telegram/Slack/Discord/Signal/iMessage/etc,
plus mobile voice and Canvas on supported platforms.
Model-agnostic: use Anthropic, OpenAI, MiniMax, OpenRouter, etc., with per-agent routing
and failover.
Local-only option: run local models so all data can stay on your device if you want.
Multi-agent routing: separate agents per channel, account, or task, each with its own
workspace and defaults.
Open source and hackable: inspect, extend, and self-host without vendor lock-in.
Build a website (WordPress, Shopify, or a simple static site).
Prototype a mobile app (outline, screens, API plan).
Organize files and folders (cleanup, naming, tagging).
Connect Gmail and automate summaries or follow ups.
It can handle large tasks, but it works best when you split them into phases and
use sub agents for parallel work.
What are the top five everyday use cases for OpenClaw?
Everyday wins usually look like:
Personal briefings: summaries of inbox, calendar, and news you care about.
Research and drafting: quick research, summaries, and first drafts for emails or docs.
Reminders and follow ups: cron or heartbeat driven nudges and checklists.
Browser automation: filling forms, collecting data, and repeating web tasks.
Cross device coordination: send a task from your phone, let the Gateway run it on a server, and get the result back in chat.
Can OpenClaw help with lead gen, outreach, ads, and blogs for a SaaS?
Yes for research, qualification, and drafting. It can scan sites, build shortlists,
summarize prospects, and write outreach or ad copy drafts.
For outreach or ad runs, keep a human in the loop. Avoid spam, follow local laws and
platform policies, and review anything before it is sent. The safest pattern is to let
OpenClaw draft and you approve.
What are the advantages vs Claude Code for web development?
OpenClaw is a personal assistant and coordination layer, not an IDE replacement. Use
Claude Code or Codex for the fastest direct coding loop inside a repo. Use OpenClaw when you
want durable memory, cross-device access, and tool orchestration.
How do I customize skills without keeping the repo dirty?
Use managed overrides instead of editing the repo copy. Put your changes in `~/.openclaw/skills/
/SKILL.md(or add a folder viaskills.load.extraDirsin~/.openclaw/openclaw.json). Precedence is
/skills>~/.openclaw/skills` > bundled, so managed overrides win without touching git. Only upstream-worthy edits should live in the repo and go out as PRs.
Can I load skills from a custom folder?
Yes. Add extra directories via skills.load.extraDirs in ~/.openclaw/openclaw.json (lowest precedence). Default precedence remains: `
/skills→~/.openclaw/skills→ bundled →skills.load.extraDirs. clawhubinstalls into./skillsby default, which OpenClaw treats as
/skills` on the next session.
How can I use different models for different tasks?
Today the supported patterns are:
Cron jobs: isolated jobs can set a model override per job.
Sub-agents: route tasks to separate agents with different default models.
On-demand switch: use /model to switch the current session model at any time.
The bot freezes while doing heavy work. How do I offload that?
Use sub-agents for long or parallel tasks. Sub-agents run in their own session,
return a summary, and keep your main chat responsive.
Ask your bot to “spawn a sub-agent for this task” or use /subagents.
Use /status in chat to see what the Gateway is doing right now (and whether it is busy).
Token tip: long tasks and sub-agents both consume tokens. If cost is a concern, set a
cheaper model for sub-agents via agents.defaults.subagents.model.
Use native openclaw skills commands or drop skills into your workspace. The macOS Skills UI isn’t available on Linux.
Browse skills at https://clawhub.com.
Terminal window
openclawskillssearch"calendar"
openclawskillsinstall
openclaw skills update —all
Install the separate `clawhub` CLI only if you want to publish or sync your own skills.
Can OpenClaw run tasks on a schedule or continuously in the background?
Yes. Use the Gateway scheduler:
Cron jobs for scheduled or recurring tasks (persist across restarts).
Heartbeat for “main session” periodic checks.
Isolated jobs for autonomous agents that post summaries or deliver to chats.
Not directly. macOS skills are gated by metadata.openclaw.os plus required binaries, and skills only appear in the system prompt when they are eligible on the Gateway host. On Linux, darwin-only skills (like apple-notes, apple-reminders, things-mac) will not load unless you override the gating.
You have three supported patterns:
Option A - run the Gateway on a Mac (simplest).
Run the Gateway where the macOS binaries exist, then connect from Linux in remote mode or over Tailscale. The skills load normally because the Gateway host is macOS.
Option B - use a macOS node (no SSH).
Run the Gateway on Linux, pair a macOS node (menubar app), and set Node Run Commands to “Always Ask” or “Always Allow” on the Mac. OpenClaw can treat macOS-only skills as eligible when the required binaries exist on the node. The agent runs those skills via the nodes tool. If you choose “Always Ask”, approving “Always Allow” in the prompt adds that command to the allowlist.
Option C - proxy macOS binaries over SSH (advanced).
Keep the Gateway on Linux, but make the required CLI binaries resolve to SSH wrappers that run on a Mac. Then override the skill to allow Linux so it stays eligible.
Create an SSH wrapper for the binary (example: memo for Apple Notes):
#!/usr/bin/env bash
set-euopipefail
execssh-Tuser@mac-host/opt/homebrew/bin/memo"$@"
Put the wrapper on PATH on the Linux host (for example ~/bin/memo).
Override the skill metadata (workspace or ~/.openclaw/skills) to allow Linux:
---
name: apple-notes
description: Manage Apple Notes via the memo CLI on macOS.
Start a new session so the skills snapshot refreshes.
Do you have a Notion or HeyGen integration?
Not built-in today.
Options:
Custom skill / plugin: best for reliable API access (Notion/HeyGen both have APIs).
Browser automation: works without code but is slower and more fragile.
If you want to keep context per client (agency workflows), a simple pattern is:
One Notion page per client (context + preferences + active work).
Ask the agent to fetch that page at the start of a session.
If you want a native integration, open a feature request or build a skill
targeting those APIs.
Install skills:
Terminal window
openclawskillsinstall
openclaw skills update —all
Native installs land in the active workspace `skills/` directory. For shared skills across agents, place them in `~/.openclaw/skills/
/SKILL.md`. Some skills expect binaries installed via Homebrew; on Linux that means Linuxbrew (see the Homebrew Linux FAQ entry above). See Skills and ClawHub.
How do I use my existing signed-in Chrome with OpenClaw?
Use the built-in user browser profile, which attaches through Chrome DevTools MCP:
Terminal window
openclawbrowser--browser-profileusertabs
openclawbrowser--browser-profileusersnapshot
If you want a custom name, create an explicit MCP profile:
Yes. See Sandboxing. For Docker-specific setup (full gateway in Docker or sandbox images), see Docker.
Docker feels limited - how do I enable full features?
The default image is security-first and runs as the node user, so it does not
include system packages, Homebrew, or bundled browsers. For a fuller setup:
Persist /home/node with OPENCLAW_HOME_VOLUME so caches survive.
Bake system deps into the image with OPENCLAW_DOCKER_APT_PACKAGES.
Install Playwright browsers via the bundled CLI:
node /app/node_modules/playwright-core/cli.js install chromium
Set PLAYWRIGHT_BROWSERS_PATH and ensure the path is persisted.
Can I keep DMs personal but make groups public/sandboxed with one agent?
Yes - if your private traffic is DMs and your public traffic is groups.
Use agents.defaults.sandbox.mode: "non-main" so group/channel sessions (non-main keys) run in Docker, while the main DM session stays on-host. Then restrict what tools are available in sandboxed sessions via tools.sandbox.tools.
Set agents.defaults.sandbox.docker.binds to ["host:path:mode"] (e.g., "/home/user/src:/src:ro"). Global + per-agent binds merge; per-agent binds are ignored when scope: "shared". Use :ro for anything sensitive and remember binds bypass the sandbox filesystem walls. See Sandboxing and Sandbox vs Tool Policy vs Elevated for examples and safety notes.
How does memory work?
OpenClaw memory is just Markdown files in the agent workspace:
Daily notes in memory/YYYY-MM-DD.md
Curated long-term notes in MEMORY.md (main/private sessions only)
OpenClaw also runs a silent pre-compaction memory flush to remind the model
to write durable notes before auto-compaction. This only runs when the workspace
is writable (read-only sandboxes skip it). See Memory.
Memory keeps forgetting things. How do I make it stick?
Ask the bot to write the fact to memory. Long-term notes belong in MEMORY.md,
short-term context goes into memory/YYYY-MM-DD.md.
This is still an area we are improving. It helps to remind the model to store memories;
it will know what to do. If it keeps forgetting, verify the Gateway is using the same
workspace on every run.
Memory files live on disk and persist until you delete them. The limit is your
storage, not the model. The session context is still limited by the model
context window, so long conversations can compact or truncate. That is why
memory search exists - it pulls only the relevant parts back into context.
Does semantic memory search require an OpenAI API key?
Only if you use OpenAI embeddings. Codex OAuth covers chat/completions and
does not grant embeddings access, so signing in with Codex (OAuth or the
Codex CLI login) does not help for semantic memory search. OpenAI embeddings
still need a real API key (OPENAI_API_KEY or models.providers.openai.apiKey).
If you don’t set a provider explicitly, OpenClaw auto-selects a provider when it
can resolve an API key (auth profiles, models.providers.*.apiKey, or env vars).
It prefers OpenAI if an OpenAI key resolves, otherwise Gemini if a Gemini key
resolves, then Voyage, then Mistral. If no remote key is available, memory
search stays disabled until you configure it. If you have a local model path
configured and present, OpenClaw
prefers local. Ollama is supported when you explicitly set
memorySearch.provider = "ollama".
If you’d rather stay local, set memorySearch.provider = "local" (and optionally
memorySearch.fallback = "none"). If you want Gemini embeddings, set
memorySearch.provider = "gemini" and provide GEMINI_API_KEY (or
memorySearch.remote.apiKey). We support OpenAI, Gemini, Voyage, Mistral, Ollama, or local embedding
models - see Memory for the setup details.
No - OpenClaw’s state is local, but external services still see what you send them.
Local by default: sessions, memory files, config, and workspace live on the Gateway host
(~/.openclaw + your workspace directory).
Remote by necessity: messages you send to model providers (Anthropic/OpenAI/etc.) go to
their APIs, and chat platforms (WhatsApp/Telegram/Slack/etc.) store message data on their
servers.
You control the footprint: using local models keeps prompts on your machine, but channel
traffic still goes through the channel’s servers.
Legacy single-agent path: `~/.openclaw/agent/*` (migrated by `openclaw doctor`).
Your **workspace** (AGENTS.md, memory files, skills, etc.) is separate and configured via `agents.defaults.workspace` (default: `~/.openclaw/workspace`).
Where should AGENTS.md / SOUL.md / USER.md / MEMORY.md live?
These files live in the agent workspace, not ~/.openclaw.
Workspace (per agent): AGENTS.md, SOUL.md, IDENTITY.md, USER.md,
MEMORY.md (or legacy fallback memory.md when MEMORY.md is absent),
memory/YYYY-MM-DD.md, optional HEARTBEAT.md.
State dir (~/.openclaw): config, credentials, auth profiles, sessions, logs,
and shared skills (~/.openclaw/skills).
Default workspace is ~/.openclaw/workspace, configurable via:
If the bot “forgets” after a restart, confirm the Gateway is using the same
workspace on every launch (and remember: remote mode uses the gateway host’s
workspace, not your local laptop).
Tip: if you want a durable behavior or preference, ask the bot to write it into
AGENTS.md or MEMORY.md rather than relying on chat history.
Put your agent workspace in a private git repo and back it up somewhere
private (for example GitHub private). This captures memory + AGENTS/SOUL/USER
files, and lets you restore the assistant’s “mind” later.
Do not commit anything under ~/.openclaw (credentials, sessions, tokens, or encrypted secrets payloads).
If you need a full restore, back up both the workspace and the state directory
separately (see the migration question above).
Yes. The workspace is the default cwd and memory anchor, not a hard sandbox.
Relative paths resolve inside the workspace, but absolute paths can access other
host locations unless sandboxing is enabled. If you need isolation, use
agents.defaults.sandbox or per-agent sandbox settings. If you
want a repo to be the default working directory, point that agent’s
workspace to the repo root. The OpenClaw repo is just source code; keep the
workspace separate unless you intentionally want the agent to work inside it.
Example (repo as default cwd):
{
agents: {
defaults: {
workspace: "~/Projects/my-repo",
},
},
}
Remote mode: where is the session store?
Session state is owned by the gateway host. If you’re in remote mode, the session store you care about is on the remote machine, not your local laptop. See Session management.
gateway.remote.token / .password do not enable local gateway auth by themselves.
Local call paths can use gateway.remote.* as fallback only when gateway.auth.* is unset.
If gateway.auth.token / gateway.auth.password is explicitly configured via SecretRef and unresolved, resolution fails closed (no remote fallback masking).
The Control UI authenticates via connect.params.auth.token (stored in app/UI settings). Avoid putting tokens in URLs.
Why do I need a token on localhost now?
OpenClaw enforces token auth by default, including loopback. If no token is configured, gateway startup auto-generates one and saves it to gateway.auth.token, so local WS clients must authenticate. This blocks other local processes from calling the Gateway.
If you really want open loopback, set gateway.auth.mode: "none" explicitly in your config. Doctor can generate a token for you any time: openclaw doctor --generate-gateway-token.
Do I have to restart after changing config?
The Gateway watches the config and supports hot-reload:
gateway.reload.mode: "hybrid" (default): hot-apply safe changes, restart for critical ones
hot, restart, off are also supported
How do I disable funny CLI taglines?
Set cli.banner.taglineMode in config:
{
cli: {
banner: {
taglineMode: "off", // random | default | off
},
},
}
off: hides tagline text but keeps the banner title/version line.
default: uses All your chats, one OpenClaw. every time.
If you want no banner at all, set env OPENCLAW_HIDE_BANNER=1.
How do I enable web search (and web fetch)?
web_fetch works without an API key. web_search requires a key for your
selected provider (Brave, Gemini, Grok, Kimi, or Perplexity).
Recommended: run openclaw configure --section web and choose a provider.
Environment alternatives:
Brave: BRAVE_API_KEY
Gemini: GEMINI_API_KEY
Grok: XAI_API_KEY
Kimi: KIMI_API_KEY or MOONSHOT_API_KEY
Perplexity: PERPLEXITY_API_KEY or OPENROUTER_API_KEY
{
plugins: {
entries: {
brave: {
config: {
webSearch: {
apiKey: "BRAVE_API_KEY_HERE",
},
},
},
},
},
tools: {
web: {
search: {
enabled: true,
provider: "brave",
maxResults: 5,
},
fetch: {
enabled: true,
},
},
},
}
Provider-specific web-search config now lives under `plugins.entries.
.config.webSearch.. Legacy tools.web.search.` provider paths still load temporarily for compatibility, but they should not be used for new configs.
Notes:
- If you use allowlists, add `web_search`/`web_fetch` or `group:web`.
- `web_fetch` is enabled by default (unless explicitly disabled).
- Daemons read env vars from `~/.openclaw/.env` (or the service environment).
Docs: [Web tools](/en/tools/web).
config.apply wiped my config. How do I recover and avoid this?
config.apply replaces the entire config. If you send a partial object, everything
else is removed.
Recover:
Restore from backup (git or a copied ~/.openclaw/openclaw.json).
If you have no backup, re-run openclaw doctor and reconfigure channels/models.
If this was unexpected, file a bug and include your last known config or any backup.
A local coding agent can often reconstruct a working config from logs or history.
How do commands propagate between Telegram, the gateway, and nodes?
Telegram messages are handled by the gateway. The gateway runs the agent and
only then calls nodes over the Gateway WebSocket when a node tool is needed:
Nodes don’t see inbound provider traffic; they only receive node RPC calls.
How can my agent access my computer if the Gateway is hosted remotely?
Short answer: pair your computer as a node. The Gateway runs elsewhere, but it can
call node.* tools (screen, camera, system) on your local machine over the Gateway WebSocket.
Typical setup:
Run the Gateway on the always-on host (VPS/home server).
Put the Gateway host + your computer on the same tailnet.
Ensure the Gateway WS is reachable (tailnet bind or SSH tunnel).
Open the macOS app locally and connect in Remote over SSH mode (or direct tailnet)
so it can register as a node.
Approve the node on the Gateway:
Terminal window
openclawdeviceslist
openclawdevicesapprove
No separate TCP bridge is required; nodes connect over the Gateway WebSocket.
Security reminder: pairing a macOS node allows `system.run` on that machine. Only
pair devices you trust, and review [Security](/en/gateway/security).
Can two OpenClaw instances talk to each other (local + VPS)?
Yes. There is no built-in “bot-to-bot” bridge, but you can wire it up in a few
reliable ways:
Simplest: use a normal chat channel both bots can access (Telegram/Slack/WhatsApp).
Have Bot A send a message to Bot B, then let Bot B reply as usual.
CLI bridge (generic): run a script that calls the other Gateway with
openclaw agent --message ... --deliver, targeting a chat where the other bot
listens. If one bot is on a remote VPS, point your CLI at that remote Gateway
via SSH/Tailscale (see Remote access).
Example pattern (run from a machine that can reach the target Gateway):
Terminal window
openclawagent--message"Hello from local bot"--deliver--channeltelegram--reply-to
Tip: add a guardrail so the two bots do not loop endlessly (mention-only, channel
allowlists, or a "do not reply to bot messages" rule).
No. One Gateway can host multiple agents, each with its own workspace, model defaults,
and routing. That is the normal setup and it is much cheaper and simpler than running
one VPS per agent.
Use separate VPSes only when you need hard isolation (security boundaries) or very
different configs that you do not want to share. Otherwise, keep one Gateway and
use multiple agents or sub-agents.
Is there a benefit to using a node on my personal laptop instead of SSH from a VPS?
Yes - nodes are the first-class way to reach your laptop from a remote Gateway, and they
unlock more than shell access. The Gateway runs on macOS/Linux (Windows via WSL2) and is
lightweight (a small VPS or Raspberry Pi-class box is fine; 4 GB RAM is plenty), so a common
setup is an always-on host plus your laptop as a node.
No inbound SSH required. Nodes connect out to the Gateway WebSocket and use device pairing.
Safer execution controls.system.run is gated by node allowlists/approvals on that laptop.
More device tools. Nodes expose canvas, camera, and screen in addition to system.run.
Local browser automation. Keep the Gateway on a VPS, but run Chrome locally through a node host on the laptop, or attach to local Chrome on the host via Chrome MCP.
SSH is fine for ad-hoc shell access, but nodes are simpler for ongoing agent workflows and
device automation.
No. Only one gateway should run per host unless you intentionally run isolated profiles (see Multiple gateways). Nodes are peripherals that connect
to the gateway (iOS/Android nodes, or macOS “node mode” in the menubar app). For headless node
hosts and CLI control, see Node host CLI.
A full restart is required for gateway, discovery, and canvasHost changes.
Is there an API / RPC way to apply config?
Yes. config.apply validates + writes the full config and restarts the Gateway as part of the operation.
Should I install on a second laptop or just add a node?
If you only need local tools (screen/camera/exec) on the second laptop, add it as a
node. That keeps a single Gateway and avoids duplicated config. Local node tools are
currently macOS-only, but we plan to extend them to other OSes.
Install a second Gateway only when you need hard isolation or two fully separate bots.
I started the Gateway via the service and my env vars disappeared. What now?
Two common fixes:
Put the missing keys in ~/.openclaw/.env so they’re picked up even when the service doesn’t inherit your shell env.
Enable shell import (opt-in convenience):
{
env: {
shellEnv: {
enabled: true,
timeoutMs: 15000,
},
},
}
This runs your login shell and imports only missing expected keys (never overrides). Env var equivalents:
OPENCLAW_LOAD_SHELL_ENV=1, OPENCLAW_SHELL_ENV_TIMEOUT_MS=15000.
I set COPILOT_GITHUB_TOKEN, but models status shows "Shell env: off." Why?
openclaw models status reports whether shell env import is enabled. “Shell env: off”
does not mean your env vars are missing - it just means OpenClaw won’t load
your login shell automatically.
If the Gateway runs as a service (launchd/systemd), it won’t inherit your shell
environment. Fix by doing one of these:
Put the token in ~/.openclaw/.env:
COPILOT_GITHUB_TOKEN=...
Or enable shell import (env.shellEnv.enabled: true).
Or add it to your config env block (applies only if missing).
Do sessions reset automatically if I never send /new?
Sessions can expire after session.idleMinutes, but this is disabled by default (default 0).
Set it to a positive value to enable idle expiry. When enabled, the next
message after the idle period starts a fresh session id for that chat key.
This does not delete transcripts - it just starts a new session.
{
session: {
idleMinutes: 240,
},
}
Is there a way to make a team of OpenClaw instances (one CEO and many agents)?
Yes, via multi-agent routing and sub-agents. You can create one coordinator
agent and several worker agents with their own workspaces and models.
That said, this is best seen as a fun experiment. It is token heavy and often
less efficient than using one bot with separate sessions. The typical model we
envision is one bot you talk to, with different sessions for parallel work. That
bot can also spawn sub-agents when needed.
Why am I seeing "LLM request rejected: messages.content.tool_use.input field required"?
This is a provider validation error: the model emitted a tool_use block without the required
input. It usually means the session history is stale or corrupted (often after long threads
or a tool/schema change).
Fix: start a fresh session with /new (standalone message).
Why am I getting heartbeat messages every 30 minutes?
Heartbeats run every 30m by default (1h when using OAuth auth). Tune or disable them:
{
agents: {
defaults: {
heartbeat: {
every: "2h", // or "0m" to disable
},
},
},
}
If HEARTBEAT.md exists but is effectively empty (only blank lines and markdown
headers like # Heading), OpenClaw skips the heartbeat run to save API calls.
If the file is missing, the heartbeat still runs and the model decides what to do.
Per-agent overrides use agents.list[].heartbeat. Docs: Heartbeat.
Do I need to add a "bot account" to a WhatsApp group?
No. OpenClaw runs on your own account, so if you’re in the group, OpenClaw can see it.
By default, group replies are blocked until you allow senders (groupPolicy: "allowlist").
If you want only you to be able to trigger group replies:
{
channels: {
whatsapp: {
groupPolicy: "allowlist",
groupAllowFrom: ["+15551234567"],
},
},
}
How do I get the JID of a WhatsApp group?
Option 1 (fastest): tail logs and send a test message in the group:
Direct chats collapse to the main session by default. Groups/channels have their own session keys, and Telegram topics / Discord threads are separate sessions. See Groups and Group messages.
How many workspaces and agents can I create?
No hard limits. Dozens (even hundreds) are fine, but watch for:
Disk growth: sessions + transcripts live under `~/.openclaw/agents/
/sessions/`.
- Token cost: more agents means more concurrent model usage.
- Ops overhead: per-agent auth profiles, workspaces, and channel routing.
Tips:
- Keep one **active** workspace per agent (`agents.defaults.workspace`).
- Prune old sessions (delete JSONL or store entries) if disk grows.
- Use `openclaw doctor` to spot stray workspaces and profile mismatches.
Can I run multiple bots or chats at the same time (Slack), and how should I set that up?
Yes. Use Multi-Agent Routing to run multiple isolated agents and route inbound messages by
channel/account/peer. Slack is supported as a channel and can be bound to specific agents.
Browser access is powerful but not “do anything a human can” - anti-bot, CAPTCHAs, and MFA can
still block automation. For the most reliable browser control, use local Chrome MCP on the host,
or use CDP on the machine that actually runs the browser.
Best-practice setup:
Always-on Gateway host (VPS/Mac mini).
One agent per role (bindings).
Slack channel(s) bound to those agents.
Local browser via Chrome MCP or a node when needed.
Models are referenced as provider/model (example: anthropic/claude-opus-4-6). If you omit the provider, OpenClaw currently assumes anthropic as a temporary deprecation fallback - but you should still explicitly set provider/model.
What model do you recommend?
Recommended default: use the strongest latest-generation model available in your provider stack.
For tool-enabled or untrusted-input agents: prioritize model strength over cost.
For routine/low-stakes chat: use cheaper fallback models and route by agent role.
Rule of thumb: use the best model you can afford for high-stakes work, and a cheaper
model for routine chat or summaries. You can route models per agent and use sub-agents to
parallelize long tasks (each sub-agent consumes tokens). See Models and
Sub-agents.
Strong warning: weaker/over-quantized models are more vulnerable to prompt
injection and unsafe behavior. See Security.
Use model commands or edit only the model fields. Avoid full config replaces.
Safe options:
/model in chat (quick, per-session)
openclaw models set ... (updates just model config)
openclaw configure --section model (interactive)
edit agents.defaults.model in ~/.openclaw/openclaw.json
Avoid config.apply with a partial object unless you intend to replace the whole config.
If you did overwrite config, restore from backup or re-run openclaw doctor to repair.
What do OpenClaw, Flawd, and Krill use for models?
These deployments can differ and may change over time; there is no fixed provider recommendation.
Check the current runtime setting on each gateway with openclaw models status.
For security-sensitive/tool-enabled agents, use the strongest latest-generation model available.
How do I switch models on the fly (without restarting)?
Use the /model command as a standalone message:
/model sonnet
/model opus
/model gpt
/model gpt-mini
/model gemini
/model gemini-flash
/model gemini-flash-lite
These are the built-in aliases. Custom aliases can be added via agents.defaults.models.
You can list available models with /model, /model list, or /model status.
/model (and /model list) shows a compact, numbered picker. Select by number:
/model 3
You can also force a specific auth profile for the provider (per session):
/model opus@anthropic:default
/model opus@anthropic:work
Tip: /model status shows which agent is active, which auth-profiles.json file is being used, and which auth profile will be tried next.
It also shows the configured provider endpoint (baseUrl) and API mode (api) when available.
How do I unpin a profile I set with @profile?
Re-run /modelwithout the @profile suffix:
/model anthropic/claude-opus-4-6
If you want to return to the default, pick it from /model (or send `/model
). Use /model status` to confirm which auth profile is active.
Can I use GPT 5.2 for daily tasks and Codex 5.3 for coding?
Yes. Set one as default and switch as needed:
Quick switch (per session):/model gpt-5.4 for daily tasks, /model openai-codex/gpt-5.4 for coding with Codex OAuth.
Default + switch: set agents.defaults.model.primary to openai/gpt-5.4, then switch to openai-codex/gpt-5.4 when coding (or the other way around).
Sub-agents: route coding tasks to sub-agents with a different default model.
Why do I see "Model ... is not allowed" and then no reply?
If agents.defaults.models is set, it becomes the allowlist for /model and any
session overrides. Choosing a model that isn’t in that list returns:
Model "provider/model" is not allowed. Use /model to list available models.
That error is returned instead of a normal reply. Fix: add the model to
agents.defaults.models, remove the allowlist, or pick a model from /model list.
Why do I see "Unknown model: minimax/MiniMax-M2.7"?
This means the provider isn’t configured (no MiniMax provider config or auth
profile was found), so the model can’t be resolved.
Fix checklist:
Upgrade to a current OpenClaw release (or run from source main), then restart the gateway.
Make sure MiniMax is configured (wizard or JSON), or that a MiniMax API key
exists in env/auth profiles so the provider can be injected.
Use the exact model id (case-sensitive): minimax/MiniMax-M2.7 or
minimax/MiniMax-M2.7-highspeed.
Can I use MiniMax as my default and OpenAI for complex tasks?
Yes. Use MiniMax as the default and switch models per session when needed.
Fallbacks are for errors, not “hard tasks,” so use /model or a separate agent.
If you reference a provider/model but the required provider key is missing, you’ll get a runtime auth error (e.g. No API key found for provider "zai").
No API key found for provider after adding a new agent
This usually means the new agent has an empty auth store. Auth is per-agent and
stored in:
~/.openclaw/agents/
/agent/auth-profiles.json
```
Fix options:
- Run `openclaw agents add
and configure auth during the wizard. - Or copyauth-profiles.jsonfrom the main agent'sagentDirinto the new agent'sagentDir`.
Do **not** reuse `agentDir` across agents; it causes auth/session collisions.
Model fallback to the next model in agents.defaults.model.fallbacks.
Cooldowns apply to failing profiles (exponential backoff), so OpenClaw can keep responding even when a provider is rate-limited or temporarily failing.
What does "No credentials found for profile anthropic:default" mean?
It means the system attempted to use the auth profile ID anthropic:default, but could not find credentials for it in the expected auth store.
Fix checklist:
Confirm where auth profiles live (new vs legacy paths)
Current: `~/.openclaw/agents/
/agent/auth-profiles.json - Legacy:/.openclaw/agent/*(migrated byopenclaw doctor) - **Confirm your env var is loaded by the Gateway** - If you set ANTHROPIC_API_KEYin your shell but run the Gateway via systemd/launchd, it may not inherit it. Put it in/.openclaw/.envor enableenv.shellEnv. - **Make sure you're editing the correct agent** - Multi-agent setups mean there can be multiple auth-profiles.jsonfiles. - **Sanity-check model/auth status** - Useopenclaw models status` to see configured models and whether providers are authenticated.
**Fix checklist for "No credentials found for profile anthropic"**
This means the run is pinned to an Anthropic auth profile, but the Gateway
can't find it in its auth store.
- **Use a setup-token**
- Run `claude setup-token`, then paste it with `openclaw models auth setup-token --provider anthropic`.
- If the token was created on another machine, use `openclaw models auth paste-token --provider anthropic`.
- **If you want to use an API key instead**
- Put `ANTHROPIC_API_KEY` in `~/.openclaw/.env` on the **gateway host**.
- Clear any pinned order that forces a missing profile:
```bash
openclaw models auth order clear --provider anthropic
```
- **Confirm you're running commands on the gateway host**
- In remote mode, auth profiles live on the gateway machine, not your laptop.
Why did it also try Google Gemini and fail?
If your model config includes Google Gemini as a fallback (or you switched to a Gemini shorthand), OpenClaw will try it during model fallback. If you haven’t configured Google credentials, you’ll see No API key found for provider "google".
Fix: either provide Google auth, or remove/avoid Google models in agents.defaults.model.fallbacks / aliases so fallback doesn’t route there.
Cause: the session history contains thinking blocks without signatures (often from
an aborted/partial stream). Google Antigravity requires signatures for thinking blocks.
Fix: OpenClaw now strips unsigned thinking blocks for Google Antigravity Claude. If it still appears, start a new session or set /thinking off for that agent.
Auth profiles: what they are and how to manage them
An auth profile is a named credential record (OAuth or API key) tied to a provider. Profiles live in:
~/.openclaw/agents/
/agent/auth-profiles.json
```
What are typical profile IDs?
OpenClaw uses provider-prefixed IDs like:
anthropic:default (common when no email identity exists)
`anthropic:
for OAuth identities - custom IDs you choose (e.g.anthropic:work`)
Can I control which auth profile is tried first?
Yes. Config supports optional metadata for profiles and an ordering per provider (`auth.order.
`). This does not store secrets; it maps IDs to provider/mode and sets rotation order.
OpenClaw may temporarily skip a profile if it's in a short **cooldown** (rate limits/timeouts/auth failures) or a longer **disabled** state (billing/insufficient credits). To inspect this, run `openclaw models status --json` and check `auth.unusableProfiles`. Tuning: `auth.cooldowns.billingBackoffHours*`.
You can also set a **per-agent** order override (stored in that agent's `auth-profiles.json`) via the CLI:
```bash
# Defaults to the configured default agent (omit --agent)
openclaw models auth order get --provider anthropic
# Lock rotation to a single profile (only try this one)
openclaw models auth order set --provider anthropic anthropic:default
# Or set an explicit order (fallback within provider)
openclaw models auth order set --provider anthropic anthropic:work anthropic:default
# Clear override (fall back to config auth.order / round-robin)
openclaw models auth order clear --provider anthropic
```
To target a specific agent:
```bash
openclaw models auth order set --provider anthropic --agent main anthropic:default
```
OAuth vs API key - what is the difference?
OpenClaw supports both:
OAuth often leverages subscription access (where applicable).
API keys use pay-per-token billing.
The wizard explicitly supports Anthropic setup-token and OpenAI Codex OAuth and can store API keys for you.
Gateway: ports, “already running”, and remote mode
Why does openclaw gateway status say "Runtime: running" but "RPC probe: failed"?
Because “running” is the supervisor’s view (launchd/systemd/schtasks). The RPC probe is the CLI actually connecting to the gateway WebSocket and calling status.
Use openclaw gateway status and trust these lines:
Probe target: (the URL the probe actually used)
Listening: (what’s actually bound on the port)
Last gateway error: (common root cause when the process is alive but the port isn’t listening)
Why does openclaw gateway status show "Config (cli)" and "Config (service)" different?
You’re editing one config file while the service is running another (often a --profile / OPENCLAW_STATE_DIR mismatch).
Fix:
Terminal window
openclawgatewayinstall--force
Run that from the same --profile / environment you want the service to use.
What does "another gateway instance is already listening" mean?
OpenClaw enforces a runtime lock by binding the WebSocket listener immediately on startup (default ws://127.0.0.1:18789). If the bind fails with EADDRINUSE, it throws GatewayLockError indicating another instance is already listening.
Fix: stop the other instance, free the port, or run with `openclaw gateway —port
`.
How do I run OpenClaw in remote mode (client connects to a Gateway elsewhere)?
Set gateway.mode: "remote" and point to a remote WebSocket URL, optionally with a token/password:
{
gateway: {
mode: "remote",
remote: {
url: "ws://gateway.tailnet:18789",
token: "your-token",
password: "your-password",
},
},
}
Notes:
openclaw gateway only starts when gateway.mode is local (or you pass the override flag).
The macOS app watches the config file and switches modes live when these values change.
The Control UI says "unauthorized" (or keeps reconnecting). What now?
Your gateway is running with auth enabled (gateway.auth.*), but the UI is not sending the matching token/password.
Facts (from code):
The Control UI keeps the token in sessionStorage for the current browser tab session and selected gateway URL, so same-tab refreshes keep working without restoring long-lived localStorage token persistence.
On AUTH_TOKEN_MISMATCH, trusted clients can attempt one bounded retry with a cached device token when the gateway returns retry hints (canRetryWithDeviceToken=true, recommendedNextStep=retry_with_device_token).
Fix:
Fastest: openclaw dashboard (prints + copies the dashboard URL, tries to open; shows SSH hint if headless).
If you don’t have a token yet: openclaw doctor --generate-gateway-token.
If remote, tunnel first: ssh -N -L 18789:127.0.0.1:18789 user@host then open http://127.0.0.1:18789/.
Set gateway.auth.token (or OPENCLAW_GATEWAY_TOKEN) on the gateway host.
In the Control UI settings, paste the same token.
If mismatch persists after the one retry, rotate/re-approve the paired device token:
openclaw devices list
`openclaw devices rotate —device
—role operator`
Still stuck? Run openclaw status --all and follow Troubleshooting. See Dashboard for auth details.
I set gateway.bind tailnet but it cannot bind and nothing listens
tailnet bind picks a Tailscale IP from your network interfaces (100.64.0.0/10). If the machine isn’t on Tailscale (or the interface is down), there’s nothing to bind to.
Fix:
Start Tailscale on that host (so it has a 100.x address), or
Switch to gateway.bind: "loopback" / "lan".
Note: tailnet is explicit. auto prefers loopback; use gateway.bind: "tailnet" when you want a tailnet-only bind.
Can I run multiple Gateways on the same host?
Usually no - one Gateway can run multiple messaging channels and agents. Use multiple Gateways only when you need redundancy (ex: rescue bot) or hard isolation.
Yes, but you must isolate:
OPENCLAW_CONFIG_PATH (per-instance config)
OPENCLAW_STATE_DIR (per-instance state)
agents.defaults.workspace (workspace isolation)
gateway.port (unique ports)
Quick setup (recommended):
Use `openclaw —profile
…per instance (auto-creates~/.openclaw-
). - Set a unique gateway.portin each profile config (or pass—portfor manual runs). - Install a per-profile service:openclaw —profile
The Gateway is a WebSocket server, and it expects the very first message to
be a connect frame. If it receives anything else, it closes the connection
with code 1008 (policy violation).
Common causes:
You opened the HTTP URL in a browser (http://...) instead of a WS client.
You used the wrong port or path.
A proxy or tunnel stripped auth headers or sent a non-Gateway request.
Quick fixes:
Use the WS URL: `ws://
:18789(orwss://…if HTTPS). 2. Don't open the WS port in a normal browser tab. 3. If auth is on, include the token/password in theconnect` frame.
If you're using the CLI or TUI, the URL should look like:
You can set a stable path via logging.file. File log level is controlled by logging.level. Console verbosity is controlled by --verbose and logging.consoleLevel.
Fastest log tail:
Terminal window
openclawlogs--follow
Service/supervisor logs (when the gateway runs via launchd/systemd):
macOS: $OPENCLAW_STATE_DIR/logs/gateway.log and gateway.err.log (default: ~/.openclaw/logs/...; profiles use `~/.openclaw-
Telegram setMyCommands fails. What should I check?
Start with logs and channel status:
Terminal window
openclawchannelsstatus
openclawchannelslogs--channeltelegram
Then match the error:
BOT_COMMANDS_TOO_MUCH: the Telegram menu has too many entries. OpenClaw already trims to the Telegram limit and retries with fewer commands, but some menu entries still need to be dropped. Reduce plugin/skill/custom commands, or disable channels.telegram.commands.native if you do not need the menu.
TypeError: fetch failed, Network request for 'setMyCommands' failed!, or similar network errors: if you are on a VPS or behind a proxy, confirm outbound HTTPS is allowed and DNS works for api.telegram.org.
If the Gateway is remote, make sure you are looking at logs on the Gateway host.
- The target channel supports outbound media and isn't blocked by allowlists.
- The file is within the provider's size limits (images are resized to max 2048px).
- `tools.fs.workspaceOnly=true` keeps local-path sends limited to workspace, temp/media-store, and sandbox-validated files.
- `tools.fs.workspaceOnly=false` lets `MEDIA:` send host-local files the agent can already read, but only for media plus safe document types (images, audio, video, PDF, and Office docs). Plain text and secret-like files are still blocked.
Treat inbound DMs as untrusted input. Defaults are designed to reduce risk:
Default behavior on DM-capable channels is pairing:
Unknown senders receive a pairing code; the bot does not process their message.
Approve with: `openclaw pairing approve —channel
[—account
]
- Pending requests are capped at **3 per channel**; checkopenclaw pairing list —channel
[—account
] if a code didn't arrive. - Opening DMs publicly requires explicit opt-in (dmPolicy: “open”and allowlist”*”`).
Run `openclaw doctor` to surface risky DM policies.
Is prompt injection only a concern for public bots?
No. Prompt injection is about untrusted content, not just who can DM the bot.
If your assistant reads external content (web search/fetch, browser pages, emails,
docs, attachments, pasted logs), that content can include instructions that try
to hijack the model. This can happen even if you are the only sender.
The biggest risk is when tools are enabled: the model can be tricked into
exfiltrating context or calling tools on your behalf. Reduce the blast radius by:
using a read-only or tool-disabled “reader” agent to summarize untrusted content
keeping web_search / web_fetch / browser off for tool-enabled agents
Should my bot have its own email, GitHub account, or phone number?
Yes, for most setups. Isolating the bot with separate accounts and phone numbers
reduces the blast radius if something goes wrong. This also makes it easier to rotate
credentials or revoke access without impacting your personal accounts.
Start small. Give access only to the tools and accounts you actually need, and expand
later if required.
Can I give it autonomy over my text messages and is that safe?
We do not recommend full autonomy over your personal messages. The safest pattern is:
Keep DMs in pairing mode or a tight allowlist.
Use a separate number or account if you want it to message on your behalf.
Let it draft, then approve before sending.
If you want to experiment, do it on a dedicated account and keep it isolated. See
Security.
Can I use cheaper models for personal assistant tasks?
Yes, if the agent is chat-only and the input is trusted. Smaller tiers are
more susceptible to instruction hijacking, so avoid them for tool-enabled agents
or when reading untrusted content. If you must use a smaller model, lock down
tools and run inside a sandbox. See Security.
I ran /start in Telegram but did not get a pairing code
Pairing codes are sent only when an unknown sender messages the bot and
dmPolicy: "pairing" is enabled. /start by itself doesn’t generate a code.
Check pending requests:
Terminal window
openclawpairinglisttelegram
If you want immediate access, allowlist your sender id or set dmPolicy: "open"
for that account.
WhatsApp: will it message my contacts? How does pairing work?
No. Default WhatsApp DM policy is pairing. Unknown senders only get a pairing code and their message is not processed. OpenClaw only replies to chats it receives or to explicit sends you trigger.
Approve pairing with:
Terminal window
openclawpairingapprovewhatsapp
List pending requests:
```bash
openclaw pairing list whatsapp
Wizard phone number prompt: it’s used to set your allowlist/owner so your own DMs are permitted. It’s not used for auto-sending. If you run on your personal WhatsApp number, use that number and enable channels.whatsapp.selfChatMode.
Chat commands, aborting tasks, and “it will not stop”
How do I stop internal system messages from showing in chat?
Most internal or tool messages only appear when verbose or reasoning is enabled
for that session.
Fix in the chat where you see it:
/verbose off
/reasoning off
If it is still noisy, check the session settings in the Control UI and set verbose
to inherit. Also confirm you are not using a bot profile with verboseDefault set
to on in config.
What is the default model for Anthropic with an API key?
In OpenClaw, credentials and model selection are separate. Setting ANTHROPIC_API_KEY (or storing an Anthropic API key in auth profiles) enables authentication, but the actual default model is whatever you configure in agents.defaults.model.primary (for example, anthropic/claude-sonnet-4-6 or anthropic/claude-opus-4-6). If you see No credentials found for profile "anthropic:default", it means the Gateway couldn’t find Anthropic credentials in the expected auth-profiles.json for the agent that’s running.