Automate browser control from Go via HTTP APIs and MCP integration.
npx skills add https://github.com/browserwing/browserwing --skill browserwing-executor
Please help me install this Agent Skill. Skill: browserwing-executor Source: https://github.com/browserwing/browserwing/tree/main Command: npx skills add https://github.com/browserwing/browserwing --skill browserwing-executor
BrowserWing Executor provides a Go-based interface to automate browser tasks over HTTP, enabling MCP integration for AI agents and automation pipelines.
Install the package, initialize the BrowserManager, create an Executor, and perform a simple navigate to https://example.com.
High-intent search queries and answers about installing and using this skill.
Browser automation from Go uses HTTP APIs to control navigation, clicks, typing, and element selection on web pages. BrowserWing Executor provides a Go interface that connects to a browser over HTTP, letting you script interactions programmatically without manual browser control.
Yes. MCP integration exposes browser automation tools that AI agents can invoke directly. BrowserWing Executor registers actions like navigation and data extraction as MCP tools, enabling agents to control browsers and extract information as part of automated workflows.
During automation, you can extract text and HTML attributes from page elements and obtain accessibility snapshots. These snapshots provide semantic structure that guides subsequent interactions, supporting both data capture and intelligent navigation through page content.
Batch execution chains multiple actions—navigate, click, type, select—into a single sequence. BrowserWing Executor processes these batched operations efficiently, reducing overhead and enabling complex workflows like login-then-scrape scenarios.
Browser automation supports both QA testing and data extraction. You can log in to sites, interact with dynamic content, and capture results. BrowserWing Executor handles these workflows through a unified Go API, making it suitable for automated testing, RPA, and web scraping tasks.
Semantic-tree support structures page elements hierarchically, allowing automation logic to navigate and interact with pages based on meaning rather than brittle selectors. This improves robustness when page layouts change and simplifies reasoning about element relationships during interaction sequences.
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