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Why this server?
This server enables mapping JavaScript error stack traces back to original source code, extracting context information to help developers locate and fix issues. This directly addresses the 'fix errors' part of the request.
Why this server?
Enables AI agents to control web browsers, which could be used to navigate to a webpage, open the developer console, and potentially assist in identifying errors.
Why this server?
Enables AI agents to interact with web browsers, including automated browsing, form filling, and element detection. This could be used to reproduce steps leading to an error in a browser environment.
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. Useful for reproducing the error scenario.
Why this server?
This server can search for code examples and documentation across various platforms, which can be helpful in finding solutions to browser console errors.
Why this server?
Enables AI to access and understand project documentation, which can be useful for understanding the context of the error and how to fix it.
Why this server?
Bridges Large Language Models with Language Server Protocol interfaces, allowing LLMs to access LSP's diagnostics for improved code suggestions and error detection.
Why this server?
Automates web accessibility scans, identifying issues that may cause errors or unexpected behavior in web applications.
Why this server?
An MCP for performing accessibility audits on webpages, so that AI can fix a11y issues
Why this server?
Integrates essential penetration testing tools into a unified natural language interface, allowing security professionals to execute and chain multiple tools through conversational commands to help debug errors.