What is OpenClaw? The AI Agent Framework Explained (2026)

What is OpenClaw?

OpenClaw is an open-source AI agent framework. It lets you create autonomous AI agents that run 24/7 on your own computer, server, or even a Raspberry Pi. Unlike chatbots that only respond when you type a message, OpenClaw agents can take action on their own: they browse the web, run shell commands, manage files, send messages through Telegram or Slack, and collaborate with other agents.

The core idea behind OpenClaw is simplicity. You do not need to write code. Instead, you create a single markdown file called SOUL.md that describes who your agent is, what it does, what tools it can use, and what rules it follows. OpenClaw reads that file, connects it to a language model like Claude, GPT-4o, or Gemini, and your agent is live.

OpenClaw is self-hosted. Your agents and data stay on your machine. There is no cloud platform you depend on, no monthly subscription to the framework, and no vendor lock-in. You own everything. The only cost is the API calls to whatever language model you choose, and even that can be zero if you use Ollama with local models.

How Does OpenClaw Work?

OpenClaw has three core components that work together: the SOUL.md configuration file, the gateway runtime, and channels. Understanding these three pieces is all you need to grasp how the entire framework operates.

SOUL.md: Your Agent's Identity

Every OpenClaw agent starts with a SOUL.md file. This is a plain markdown document that acts as the agent's complete job description. It defines the agent's name, role, personality, rules, available tools, and instructions for handing off work to other agents. Think of it as writing a brief for a new team member, except the team member is an AI.

# Analytics Agent

## Role
You are a data analyst for a SaaS product.
Monitor key metrics, flag anomalies,
and deliver daily reports.

## Personality
- Data-driven and precise
- Explains numbers in plain language
- Proactive about surfacing insights

## Rules
- ALWAYS respond in English
- Include specific numbers, never vague claims
- Flag any metric that drops more than 20%
- Send daily summary at 9:00 AM

## Tools
- Use Browser to check dashboards
- Use Shell to run analytics scripts
- Use Slack to post reports

## Handoffs
- Escalate revenue drops to @ProjectManager

That is the entire configuration. No Python classes, no YAML files, no boilerplate code. The SOUL.md file is human-readable and editable by anyone on your team.

The Gateway: Your Agent's Runtime

The gateway is the execution engine that brings your SOUL.md to life. When you run openclaw gateway start, it loads your agent configurations, connects to the language model provider, and starts listening for messages. The gateway handles session management, tool execution, agent-to-agent routing, and message delivery. It runs locally on port 18789 by default.

Channels: Where Your Agent Lives

Channels are the communication interfaces that connect your agent to the outside world. OpenClaw supports WhatsApp, Telegram, Discord, Slack, Signal, and iMessage out of the box. You enable a channel by adding it to your configuration and providing a bot token. Once connected, your agent receives messages from that channel, processes them through the language model, uses its tools if needed, and sends a response back through the same channel.

What Can You Do with OpenClaw?

OpenClaw agents are not limited to answering questions. They take action, run on schedules, and handle real work. Here are four practical use cases that show what the framework can do.

These are not theoretical examples. The OpenClaw community runs agents like these every day on Mac Minis, Linux servers, VPS instances, and Raspberry Pi units. The framework gives agents access to the same tools a human operator would use: a web browser, a terminal, file system access, and messaging channels. If you want to deploy one of these agents without manual configuration, CrewClaw generates a ready-to-run package in minutes.

OpenClaw Architecture

The architecture follows a clean pipeline: your SOUL.md defines the agent, the gateway runs it, and channels deliver messages to users. Here is the full data flow from configuration to conversation.

For multi-agent setups, the gateway also handles agent-to-agent communication. When one agent @mentions another, the gateway routes the message internally without it ever leaving your machine. An agents.md file in your project root defines which agents exist, their SOUL.md paths, and their assigned models.

Supported Models

OpenClaw is model-agnostic. You choose which language model powers each agent, and you can assign different models to different agents based on their role and requirements.

A common pattern is to use Claude or GPT-4o for agents that handle complex reasoning, and Ollama with a local model for agents that process sensitive data. You configure the model provider once in your project settings, and each agent inherits it unless overridden in its own configuration. Switching between providers is a one-line change.

How to Get Started

Getting your first OpenClaw agent running takes less than five minutes. You need Node.js 22 or later installed on your machine. Here are the steps.

nvm install 22 && nvm use 22
npx openclaw onboard

# MyAgent

## Role
You are a [role description here].

## Rules
- ALWAYS respond in English
- [Your specific rules]

## Tools
- Use Browser to research topics
- Use Shell to run commands

# Claude (Anthropic)
export ANTHROPIC_API_KEY=sk-ant-...

# GPT-4o (OpenAI)
export OPENAI_API_KEY=sk-...

# Local models (free)
ollama pull llama3

openclaw gateway start

That is it. Your agent is running. You can interact with it through the terminal, connect it to Telegram or Slack, or send messages through the REST API. If you want to skip the manual setup entirely, CrewClaw generates a complete deploy package with your SOUL.md, channel configuration, and deployment scripts included.

OpenClaw vs Other Frameworks

The AI agent space includes several frameworks. Here is how OpenClaw compares to the most popular alternatives at a glance.

The key difference is that OpenClaw is a ready-to-use agent runtime. You configure agents in markdown and run them immediately. LangChain, CrewAI, and AutoGen are developer libraries that require writing Python code. Visual tools like n8n handle trigger-based automations but lack the autonomous reasoning that language model agents provide. OpenClaw sits in the middle: as powerful as code-based frameworks, but as accessible as no-code tools.

For detailed side-by-side comparisons, read our guides on OpenClaw vs CrewAI and OpenClaw vs LangChain.

Skip the Setup with CrewClaw

If you want an OpenClaw agent without writing the SOUL.md yourself, CrewClaw does it for you. Pick a role, select your integrations, and CrewClaw generates a complete deploy package: your SOUL.md configuration, channel setup, deployment scripts, and everything you need to go from zero to a running agent.

The entire process takes under two minutes. No terminal commands, no file editing, no configuration debugging. CrewClaw handles the setup so you can focus on what your agent actually does.

Frequently Asked Questions