A high-performance browser automation skill that enables AI agents to control web browsers via the Model Context Protocol.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install playwright-mcp
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install playwright-mcp using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Playwright MCP Browser Automation?
The Playwright MCP skill is a specialized toolset designed to give AI agents full control over web browsers like Chromium, Firefox, and WebKit. By utilizing the Model Context Protocol, this skill allows agents to perform actions that were previously manual, such as navigating complex single-page applications, filling out multi-step forms, and extracting real-time data from the live web. This integration within the Openclaw Skills ecosystem ensures that developers can build agents capable of sophisticated web interaction with minimal configuration.
Built on top of the industry-standard Playwright library, this skill provides a secure and programmable environment for web exploration. It bridges the gap between static LLM knowledge and the dynamic nature of the internet, making it an essential component for any developer looking to expand the capabilities of their AI coding assistants through Openclaw Skills.
Playwright MCP Browser Automation Use Cases
- Automating data extraction from dynamic websites that require JavaScript rendering.
- Performing automated UI testing and verification workflows directly through an AI agent.
- Managing web-based accounts and performing form submissions automatically.
- Generating screenshots and visual snapshots of web pages for documentation or debugging.
- Interacting with internal web tools and dashboards to gather operational data.
How Playwright MCP Browser Automation Works
- The Openclaw Skills environment triggers the Playwright MCP server which listens for incoming tool requests.
- The AI agent identifies a web-based task and selects the appropriate browser tool, such as browser_navigate or browser_click.
- The MCP server initializes a browser instance and creates a new page context to execute the requested command.
- Playwright performs the action on the DOM, handling waits and timeouts to ensure the page is in the correct state.
- The results, including extracted text, console logs, or execution status, are passed back to the agent as structured context.
- The browser context is maintained or closed based on the workflow requirements to optimize resource usage.
Playwright MCP Browser Automation Setup
To get started with this skill, install the necessary NPM package and browser binaries:
npm install -g @playwright/mcp
npx playwright install chromium
You can then run the server using npx:
npx @playwright/mcp --headless
Playwright MCP Browser Automation Data Schema & Taxonomy
The skill manages browser data and interactions using a structured approach to ensure the AI agent receives clear, actionable information. This data organization is a core part of the Openclaw Skills experience:
| Component | Type | Description |
|---|---|---|
| Selectors | String | CSS or XPath selectors used to target specific DOM elements for interaction. |
| Page Snapshots | Object | A structured representation of the accessible DOM tree for agent comprehension. |
| Evaluation Results | JSON | The output from custom JavaScript executed within the browser context. |
| Configuration | Flags | Parameters like --viewport-size and --user-agent that define the browser environment. |
Playwright MCP Browser Automation Advanced Features
- Multi-engine support allowing execution across Chromium, WebKit, and Firefox for cross-browser automation.
- Granular security controls including allowed-hosts and blocked-origins to restrict agent navigation to trusted domains.
- Custom JavaScript evaluation via browser_evaluate for complex data parsing and page manipulation.
- Support for capturing media artifacts like videos, traces, and screenshots for detailed auditing.
- Headless and headed mode toggling to assist in both automated production tasks and local debugging within Openclaw Skills.
SKILL.md
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