How to Get Started with Openclaw: A Clear Installation Guide

Getting started with a new open-source tool can be intimidating—especially when the documentation assumes more background knowledge than you have. This guide aims to be the clearest possible introduction to installing and configuring Openclaw, the open-source AI agent framework for web automation and research.

We will walk through every step from system requirements to running your first agent, with explanations for each decision along the way.

Before You Start: What You Need to Know

What Openclaw Does

Openclaw is a framework for building AI agents that can browse the web autonomously. You give it a task (“find pricing information for these 5 products”), and it navigates websites, extracts information, and returns structured results.

What Openclaw Requires

Openclaw is a developer tool. You will need:

• Comfort with the command line (terminal)
• Basic Python knowledge (helpful but not strictly required for simple tasks)
• An LLM API key (OpenAI, Anthropic, or another supported provider)
• A computer with at least 4GB of RAM (8GB+ recommended)

Time Estimate

From start to running your first agent: approximately 30–60 minutes, depending on your download speed and familiarity with the tools.

System Requirements

Operating System

Openclaw runs on:

• macOS 12+ (Intel or Apple Silicon)
• Linux (Ubuntu 20.04+, Debian 11+, or equivalent)
• Windows 10+ (WSL2 recommended for best experience)

Software Dependencies

You will need these installed before setting up Openclaw:

Software	Minimum Version	How to Check
Python	3.9+	python --version or python3 --version
pip	Latest	pip --version
Node.js	18+	node --version
Git	Any recent version	git --version

Installing Dependencies

If any of the above are missing:

Python:

• macOS: brew install python (with Homebrew) or download from python.org
• Linux: sudo apt install python3 python3-pip
• Windows: Download from python.org or use Windows Store

Node.js:

• All platforms: Download from nodejs.org or use nvm (Node Version Manager)

Git:

• macOS: brew install git or install Xcode Command Line Tools
• Linux: sudo apt install git
• Windows: Download from git-scm.com

Step 1: Get an LLM API Key

Openclaw uses large language models for decision-making. You need an API key from a supported provider.

Option A: OpenAI

1. Go to platform.openai.com
2. Create an account or sign in
3. Navigate to API Keys
4. Create a new API key
5. Copy the key (you will not be able to see it again)

Option B: Anthropic

1. Go to console.anthropic.com
2. Create an account or sign in
3. Navigate to API Keys
4. Create a new key
5. Copy the key

Cost Expectations

For testing and development, expect to spend $1–$5 on API calls. Each agent task typically costs $0.001–$0.01 in API calls, so your initial testing budget is very modest.

Step 2: Clone the Repository

Open your terminal and navigate to where you want to install Openclaw:

# Navigate to your preferred directory
cd ~/projects  # or wherever you keep code

# Clone the repository
git clone https://github.com/openclaw/openclaw.git

# Enter the project directory
cd openclaw

Step 3: Create a Virtual Environment

A virtual environment keeps Openclaw’s dependencies separate from your other Python projects:

# Create a virtual environment
python3 -m venv venv

# Activate it
# On macOS/Linux:
source venv/bin/activate

# On Windows:
.\venv\Scripts\activate

You should see (venv) at the beginning of your terminal prompt, confirming the virtual environment is active.

Step 4: Install Openclaw

Install Openclaw and its Python dependencies:

pip install -r requirements.txt

This may take a few minutes as it downloads and installs all required packages.

Step 5: Install Browser Components

Openclaw uses Playwright for browser automation. Install the required browsers:

playwright install chromium

This downloads a version of Chromium that Playwright controls. It is separate from your regular browser and will not affect your normal browsing.

Step 6: Configure Your API Key

Set your LLM API key as an environment variable:

# For OpenAI:
export OPENAI_API_KEY="sk-your-key-here"

# For Anthropic:
export ANTHROPIC_API_KEY="sk-ant-your-key-here"

To make this persistent (so you do not need to set it every time):

macOS/Linux: Add the export line to your ~/.bashrc, ~/.zshrc, or ~/.profile file.

Windows: Use System Properties > Environment Variables.

Alternatively, if Openclaw supports a .env file:

# Create a .env file in the project directory
echo 'OPENAI_API_KEY=sk-your-key-here' > .env

Step 7: Verify the Installation

Run a quick verification to ensure everything is set up correctly:

python -c "from openclaw import Agent; print('Openclaw installed successfully!')"

If this prints the success message, you are ready to create your first agent.

Step 8: Run Your First Agent

Create a simple task to verify everything works end-to-end:

# first_agent.py
from openclaw import Agent

# Create an agent
agent = Agent()

# Define a simple task
result = agent.run({
    "objective": "Go to example.com and tell me what the page title is",
    "target_url": "https://example.com"
})

print("Result:", result)

Run it:

python first_agent.py

You should see the agent navigate to example.com and return the page title. If this works, your installation is complete and functional.

Step 9: Try a More Practical Task

Now try something more useful:

# research_agent.py
from openclaw import Agent

agent = Agent()

result = agent.run({
    "objective": "Search for 'open source AI agents' on Google and list the top 5 organic results with their titles and URLs",
    "target_url": "https://www.google.com",
    "data_schema": {
        "title": "string",
        "url": "string",
        "description": "string"
    }
})

for item in result:
    print(f"Title: {item['title']}")
    print(f"URL: {item['url']}")
    print(f"Description: {item['description']}")
    print("---")

Configuration Options

Openclaw likely supports various configuration options. Common settings include:

LLM Configuration

agent = Agent(
    model="gpt-4",          # or "claude-3-opus", etc.
    temperature=0.1,         # Lower = more deterministic
    max_tokens=2000          # Maximum response length
)

Browser Configuration

agent = Agent(
    headless=True,           # True = no visible browser window
    timeout=30,              # Seconds to wait for page loads
    viewport={"width": 1280, "height": 720}
)

Agent Behavior

agent = Agent(
    max_steps=20,            # Maximum navigation steps
    rate_limit=5,            # Seconds between requests
    screenshot=True          # Capture screenshots at each step
)

Project Structure

Understanding the project structure helps when you need to customize or troubleshoot:

openclaw/
├── openclaw/          # Core framework code
│   ├── agent.py       # Main agent logic
│   ├── browser.py     # Browser automation
│   ├── llm.py         # LLM integration
│   └── extractors/    # Data extraction modules
├── examples/          # Example scripts and tasks
├── tests/             # Test suite
├── docs/              # Documentation
├── requirements.txt   # Python dependencies
├── .env.example       # Example environment configuration
└── README.md          # Getting started guide

Troubleshooting Common Issues

”Module not found” errors

Ensure your virtual environment is activated:

source venv/bin/activate  # macOS/Linux

If the error persists, reinstall dependencies:

pip install -r requirements.txt

Browser installation fails

Try installing a specific browser:

playwright install --with-deps chromium

The --with-deps flag installs system-level dependencies that Playwright needs.

API key errors

Verify your key is set:

echo $OPENAI_API_KEY  # Should print your key

If empty, re-export the key or check your .env file.

Timeout errors

Increase the timeout setting and check your internet connection:

agent = Agent(timeout=60)  # 60 seconds

Agent produces incorrect results

• Make your task objective more specific
• Define a clear data schema
• Try a simpler task first to verify the agent is working
• Check the agent’s logs for decision-making details

Next Steps

Once your installation is working:

1. Explore the examples directory — The repository likely includes example scripts for common tasks
2. Read the documentation — Understanding the full API gives you more control
3. Join the community — Check for Discord, GitHub Discussions, or other community channels
4. Build incrementally — Start with simple tasks and gradually increase complexity
5. Contribute back — If you fix bugs or add features, consider contributing to the project

For users who want to combine Openclaw’s web automation capabilities with broader AI tools for analysis and collaboration, Flowith offers a platform where you can bring web research outputs into AI-powered workflows, making it easy to go from data collection to insight.

References

• Openclaw GitHub Repository and Documentation
• Playwright Documentation
• Python Virtual Environments Guide
• OpenAI API Documentation
• Anthropic API Documentation
• Git Basics