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What Is OpenClaw? The Open-Source Personal AI Assistant You Run On Your Own Devices

OpenClaw is an open-source personal AI assistant that runs locally on your hardware and answers you through WhatsApp, Telegram, Signal, or any chat app you already use. It reached 247k GitHub stars in weeks. Here is what it is, how it works, and how to get started.

Jun 24, 2026·9 min read·Yash Thakker
OpenClawAI AgentsOpen SourcePersonal AIDeveloper Tools
What Is OpenClaw? The Open-Source Personal AI Assistant You Run On Your Own Devices

In November 2025, Peter Steinberger — the developer behind the PDF SDK used in Dropbox, Slack, and Box — pushed a side project to GitHub called Warelay. He was burned out on SaaS and wanted a personal AI that ran on his own machines, answered him through the chat apps he already used, and did not hand his data to a third party.

By March 2026, it had 247,000 GitHub stars and 47,700 forks. Renamed twice (first to Moltbot, then to OpenClaw after a trademark dispute), it became one of the fastest-growing open-source projects ever recorded. Steinberger joined OpenAI in February 2026 to work on bringing agents to everyone; OpenClaw moved to an independent foundation and stayed open.

This is the complete guide to what OpenClaw is, how it works, and how to set it up.

The one-sentence version

OpenClaw is a local-first AI gateway that runs on your machine, connects to any messaging channel you already use, and extends what it can do through installable claws.

You bring the AI model (Claude, GPT-5.5, DeepSeek, a local Ollama model — your choice). OpenClaw handles the routing, memory, sessions, and tool execution. Your messages go in through Telegram or Signal or WhatsApp; answers come back the same way.

Why it took off

Two problems that most AI products do not solve:

The interface problem. Most AI assistants force you into a web interface or a dedicated app. OpenClaw answers you on the channels you are already in. You message your Telegram bot at 2am and get a real answer. No new app to open.

The data problem. Every message you send to a hosted AI is training data for someone else's model or is stored on someone else's server. OpenClaw runs on your machine. The conversation history stays local. The model call goes to your API key, not through a middleman.

Those two properties — answer me where I already am, don't touch my data — turned out to be exactly what a large slice of developers and power users wanted but could not get anywhere else.

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How OpenClaw works

OpenClaw has three layers:

Channels — the messaging surfaces where you send and receive messages. Telegram, Signal, WhatsApp, Discord, Slack, iMessage, and 20+ others. Each channel registers as an inbox. One OpenClaw instance can handle messages from all of them at once.

Gateway — the local control plane. Routes each incoming message to the right session and agent, manages tool execution, handles memory, and streams responses back to the channel. Runs as a Node.js process on your machine.

Skills (claws) — installable capability packs that extend what the agent can do. Each claw is a directory with a SKILL.md file: YAML frontmatter naming the skill, plus natural-language instructions that the model reads to understand how to use it. Claws can wrap web search, file access, API calls, CLI tools, or any workflow you can describe in markdown.

The model — Claude, GPT-5.5, DeepSeek, or a local Ollama model — reads your message, reads any relevant skill instructions, executes tool calls (web search, file read, shell command, API call), and returns a response. All of this runs locally except the model inference itself, which goes to your chosen provider's API.

What a claw actually is

A claw is a markdown file with instructions. Here is the anatomy of a minimal one:

---
name: github
description: Read and comment on GitHub pull requests, issues, and repositories.
tools: [web_fetch, exec]
---

When the user asks about a GitHub PR or issue, fetch the URL and read the content.
Use `gh` CLI for write actions — opening PRs, posting comments, approving reviews.
Always confirm before making write operations.

When you ask something like "summarize the open PRs on my repo", OpenClaw matches your request to the github skill's description, loads the instructions into context, and follows them. You do not have to invoke skills by name — the model figures out which skill applies based on your request.

Skills can be global (available to all agents) or workspace-scoped (only for a specific agent config). They can include supporting files — scripts, templates, reference docs — alongside the SKILL.md.

Supported models and providers

OpenClaw is model-agnostic. At the gateway config level, you point it at any provider:

ProviderNotes
Anthropic ClaudeClaude 4.x / Fable 5 — best for complex reasoning and long context
OpenAI GPT-5.5 / GPT-5.5-CyberStrong general performance
DeepSeekCost-efficient alternative; popular in the community
Google GeminiLong-context option
OllamaRun models locally — no API cost, fully offline
Any OpenAI-compatible endpointCustom deployments, self-hosted models

You switch models per-agent or per-workspace — your personal assistant can run on Claude while a coding agent runs on DeepSeek for cost reasons.

Setting up OpenClaw

Requirements

  • Node 24 (recommended) or Node 22 LTS (22.19+)
  • An API key for your chosen AI model
  • 5 minutes

Install and initialize

npm install -g openclaw
# or
npx openclaw@latest onboard

The onboard command walks you step by step through:

  1. Choosing a model provider and entering your API key
  2. Setting up your first channel (Telegram is recommended for first-timers)
  3. Configuring a workspace directory
  4. Installing a starter set of claws

Set up Telegram (fastest path)

Telegram is the simplest channel to start with:

  1. Message @BotFather on Telegram → /newbot → follow prompts → copy your bot token
  2. In your OpenClaw config, set TELEGRAM_BOT_TOKEN=<your_token>
  3. Run openclaw serve
  4. Message your bot

Your messages go to your local OpenClaw process. The gateway handles the session and routes to your configured model.

Set up Signal, WhatsApp, or other channels

Each channel has its own transport configuration. Signal requires a Signal registration; WhatsApp needs a Baileys bridge or Meta Cloud API access. See the official docs at docs.openclaw.ai for channel-specific setup.

Installing claws

ClawHub (clawhub.ai) is the official skill registry with 2,857+ claws (post-security audit). Install via CLI:

# Install into current workspace
openclaw skills install github

# Install globally (available to all agents)
openclaw skills install github --global

# Browse categories
openclaw skills search "web search"
openclaw skills search "memory"

The ClawHub UI lets you browse by category, sort by downloads and stars, and read changelogs. Every skill has a VirusTotal scan report — check it before installing community claws, especially for write-enabled skills.

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Core built-in tools

Before installing any claws, OpenClaw ships with a base set of tools:

ToolWhat it does
readRead files from your filesystem
writeWrite and edit files
execRun shell commands
web_searchSearch the web (12 providers, auto-selects based on available API keys)
web_fetchFetch and read any URL
browserControl a browser — click buttons, fill forms, take screenshots
memoryStore and recall facts across sessions

These tools are what claws can call. When you install a claw, it declares which tools it uses in its tools: frontmatter field — so you know upfront what filesystem or network access a skill requires.

Web search providers

OpenClaw supports 12 web search providers. If no provider is explicitly configured, it auto-detects based on which API keys you have set, checking in this priority order:

Brave → MiniMax → Gemini → Grok → Kimi → Perplexity → Firecrawl → Exa → Tavily → DuckDuckGo → Ollama → SearXNG

DuckDuckGo requires no API key and works out of the box. Brave and Perplexity are the most popular community choices for quality. Firecrawl and Exa are popular for deep research tasks.

Memory and sessions

OpenClaw maintains session state across messages within a conversation. The memory system stores facts, preferences, and context in local SQLite — not on any external server.

Claws like memory-wiki (one of the highest-rated on ClawHub) teach the agent patterns for proactively storing and recalling context: your preferences, project details, recurring facts. Agents with good memory setups adapt to your workflow over time in ways that stateless chat UIs cannot.

BirdClaw and OpenClaw: how they relate

BirdClaw is Peter Steinberger's separate project for local Twitter/X management — a local SQLite database for your tweets, DMs, likes, and bookmarks with AI digests and a clean web UI. It ships with its own SKILL.md in its .agents/skills/birdclaw directory, which means BirdClaw-aware tasks can be wired into OpenClaw as a claw.

The two projects share the same local-first philosophy and the same author. BirdClaw handles the data layer for your Twitter history; an OpenClaw agent with the BirdClaw claw can query it, triage mentions, and generate digests through your preferred messaging channel.

See the companion guide: BirdClaw: The Local Twitter Workspace for Power Users.

The skill security situation

In January 2026, researchers at Koi Security uncovered ClawHavoc — a coordinated attack campaign that planted 341 malicious skills on ClawHub using typo-squatting. ClawHub removed 2,419 suspicious skills, partnered with VirusTotal for automatic scanning, and the registry shrank from 5,705 to ~3,286 clean skills.

The practical guidance:

  • Install skills from verified publishers (openclaw org, well-known authors with high star counts)
  • Check the VirusTotal report on any skill before installing
  • Pay attention to which tools a skill declares — a skill claiming to need exec for what should be a read-only task is a red flag
  • Prefer workspace-scoped installs over --global for skills from unknown publishers

OpenClaw vs alternatives

OpenClawClaude DesktopChatGPT Desktopn8n
Where you interactAny chat app you already useClaude Desktop appChatGPT appWeb UI / webhooks
Data stays local✅Partial❌Self-hosted option
Model choiceAnyClaude onlyOpenAI onlyAny
Skill/plugin ecosystem5,400+ clawsMCP serversGPTs400+ nodes
Self-hosted✅❌❌✅
CostAPI cost onlyClaude subscriptionOpenAI subscriptionFree/paid

The strongest OpenClaw argument is the channel flexibility and the bring-your-own-model approach. If you live in Telegram and want Claude to answer you there — with access to your files, web search, and custom skills — OpenClaw is the clearest path to that.

What it can do out of the box

Without installing any claws, a fresh OpenClaw with a good model can:

  • Answer questions using web search (built-in)
  • Read and write local files
  • Run shell commands with confirmation
  • Fetch and summarize web pages
  • Remember context across a conversation session

With popular claws installed:

  • Manage GitHub PRs and issues
  • Summarize and search your Obsidian vault
  • Triage Twitter/X with BirdClaw
  • Send Slack messages
  • Read and draft emails (Gmail / Outlook claws)
  • Control a browser for form-filling and web automation
  • Search your documents with Notion or Confluence claws

Getting started now

# Install
npm install -g openclaw

# Start onboarding
openclaw onboard

# After setup: start the gateway
openclaw serve

# Install your first claw
openclaw skills install github --global
openclaw skills install web-search --global

The full documentation is at docs.openclaw.ai. The skill registry is at clawhub.ai. The source code is at github.com/openclaw/openclaw (MIT license).

For a deep dive on available claws, read the companion post: Top 25 OpenClaw Claws Worth Installing in 2026.

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OpenClaw reached 247k GitHub stars in weeks. But what do you actually do with it? Here are the 10 most powerful real-world workflows OpenClaw users are running in 2026 — from Twitter/X triage via BirdClaw and multi-channel messaging to browser automation, document research, and Notion automation.

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Jun 24, 2026

Hermes Agent vs OpenClaw: Which Open-Source AI Agent Should You Use in 2026?

Hermes Agent (188k stars, Nous Research) and OpenClaw (247k stars, Peter Steinberger / OpenClaw Foundation) are both local-first, model-agnostic, MIT-licensed agent runtimes. But they have fundamentally different architectures: Hermes packages a learning loop around a messaging gateway, OpenClaw packages an agent around a messaging gateway. That difference drives everything else.