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Why this server?
Enables AI agents to control web browsers via a standardized interface for operations like launching, interacting with, and closing browsers, which could be helpful for identifying errors.
Why this server?
An MCP server that connects to your React Native application debugger, which would be helpful to find console errors in react native
Why this server?
A Model Context Protocol server that enables LLMs to interact with web pages, take screenshots, generate test code, scrape web pages, and execute JavaScript in a real browser environment - all of which can be used to find errors during frontend builds.
Why this server?
Enables AI agents to interact with web browsers using natural language, featuring automated browsing, form filling, vision-based element detection, and structured JSON responses for systematic browser control, potentially revealing console errors.
Why this server?
An MCP server paired with a Firefox extension that enables LLM clients to control the user's browser, supporting tab management, history search, and content reading which can be used to find browser errors.
Why this server?
A tool that captures browser console logs and makes them available in Cursor IDE through the Model Context Protocol (MCP), allowing direct access to error messages.
Why this server?
Provides accessibility testing capabilities, helping identify accessibility issues in web applications. This can indirectly help in finding layout errors.
Why this server?
Provides HTML file preview and analysis capabilities, useful for debugging frontend issues.
Why this server?
Allows AI assistants to use Google's lighthouse tool to measure perf metrics for your webpage. Then run an agentic loop and get the assistants to optimize those metrics!
Why this server?
Allows AI models to run JavaScript/TypeScript code, supporting both one-time script execution and stateful REPL sessions, which could be useful for executing debugging scripts in a browser-like environment.