- Browser Control
Browser Control
Stop feeding your agent raw HTML. BrowserControl gives LLMs true visual grounding with Set of Marks (SoM), letting them click exactly what they see without hallucinating selectors. With built-in developer tools, session recording, and persistent logins, it transforms web automation from a brittle guessing game into a reliable, human-like capability. Give your agent eyes, not just code.
Overview
What is BrowserControl?
BrowserControl is a vision-first browser control tool designed for AI agents, enabling them to interact with web pages in a human-like manner without relying on HTML scraping or DOM guessing.
How to use BrowserControl?
To use BrowserControl, set up the MCP server and utilize commands to navigate and interact with web pages using numbered elements instead of traditional selectors.
Key features of BrowserControl?
- Vision-first interaction with fully rendered web pages.
- Persistent browser sessions that maintain login states and history.
- Built-in developer tools for debugging and performance metrics.
- Session recording for replay and inspection.
- Zero extra AI cost with no external calls required.
Use cases of BrowserControl?
- Autonomous web research.
- Automated form filling.
- End-to-end testing of web applications.
- Debugging browser-based applications.
- Agent-driven quality assurance workflows.
FAQ from BrowserControl?
- Can BrowserControl work offline?
Yes! BrowserControl operates fully offline without needing external vision APIs.
- Is BrowserControl suitable for production use?
Yes! It is production-ready and actively developed with a stable status.
- What programming language is used?
BrowserControl is built with Python 3.11 and utilizes Playwright for browser automation.
Server Config
{
"mcpServers": {
"browsercontrol": {
"command": "python",
"args": [
"-m",
"browsercontrol"
]
}
}
}Project Info
Created At
6 months agoUpdated At
6 months agoAuthor Name
adityasasidharStar
-Language
-License
-Category
browser-automation
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