BrowserWing is an open-source browser automation platform designed to facilitate the automation of web tasks with AI-powered capabilities. It serves as a bridge between artificial intelligence and the web, offering instant setup, extensive customization, and control over automation workflows. The platform is positioned for developers and technical professionals seeking to record, replay, and automate browser-based processes efficiently.
Key features of BrowserWing include visual recording, which allows users to capture specific workflows directly within the browser for tailored automation needs. The tool supports importing scripts from the community or personal collections, enabling users to extend its functionality according to their requirements. Integration with multiple large language model (LLM) providers is available, equipping the platform with advanced AI capabilities for intelligent assistance in automation tasks.
BrowserWing is compatible with Windows, macOS, and Linux, ensuring cross-platform usability. md to enhance LLMs with browser automation skills. Additionally, BrowserWing integrates with a range of popular tools and platforms, including GitHub, VS Code, Postman, Spotify, LinkedIn, WordPress, Facebook, and Twitter.
The platform is open source and free to use, making it accessible for a wide range of users. BrowserWing is designed for instant integration and limitless customization, appealing to developers who require robust browser automation solutions and value community-driven extension and support.
In the Other dev tools space, BrowserWing takes a focused approach. It focuses on automating repetitive browser tasks and workflows with AI assistance and scriptable automation. BrowserWing is an open-source project aimed at developers and QA engineers. BrowserWing is open source under the MIT license. It ships for the web, Windows, macOS, and Linux.
BrowserWing first shipped in 2025. The project is developed in the open on GitHub with 1.3k stars and 49 commits in the last 90 days. Key capabilities include visual recording, script import, and cross-platform. It exposes integrations via an MCP server.
Summary written by a language model from the project’s public pages.
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