"Using a Browser with Dev Tools to Debug a Web Application" matching MCP servers:

Enables agents to inspect localhost web applications through Chrome DevTools Protocol by listing Chrome targets, attaching to a page, capturing and querying network, console, navigation, and WebSocket events, and managing ephemeral sessions.

Bridges web browsers and Claude Code for seamless debugging workflows by receiving debug data from browser widgets and exposing it to Claude Code via MCP protocol.

A smart debugging agent that remembers errors, automatically diagnoses issues, and accumulates solutions for faster resolution.

Enables systematic investigation of VMware errors and events by correlating event timelines, ranking root-cause hypotheses, and suggesting next diagnostic steps.

Enables AI agents to directly inspect and debug embedded hardware: reading/writing serial ports and bus devices, auto-detecting baud rates, parsing Modbus/NMEA/custom binary frames, plus diagnosing failures through a 45-rule fault-pattern library, error-code tables, and compile/flash error translation. Also provides pin-conflict checking, register and Cortex-M fault decoding, pre-validated driver and component selection libraries, board knowledge, and guarded flashing with post-flash byte-level verification.

An MCP server that uses SWI-Prolog for logical deduction to find root causes of errors in service dependencies, enabling root cause analysis, impact analysis, and cycle detection.

Enables AI-powered debugging through structured logging with pattern recognition and intelligent analysis. Allows applications to write structured logs and receive actionable debugging insights based on error patterns and frequency analysis.

Enables debugging Symfony applications by inspecting profiler data through a standalone MCP server.

Enables Windows-based AI assistants to run Oculus/Meta Quest Link diagnostics, capture VR screenshots and telemetry, inspect headset/controller state, and apply reversible performance-tuning and Link settings.

An MCP server that provides cost and reliability observability for LLM and agent workflows. It records model calls and allows querying and aggregating telemetry data through MCP tools.

Enables AI agents to monitor and debug browser runtime errors, console logs, and page diagnostics in real time via a Chrome extension and local MCP server.

Enables live website health checks including TLS, HTTPS, and security headers, returning an A-F grade with specific fixes.

MCP server that exposes 31 OSINT checks from Lissy93/web-check as tools for website analysis, including SSL, DNS, headers, WHOIS, and security presets. Enables natural-language-driven web recon and health checks.

Captures browser console messages (log, warn, error, etc.) and makes them available to AI language models like Claude Code and Gemini CLI for seamless debugging and development.

An MCP server for managing and monitoring Docker, Docker Compose, and Kubernetes environments alongside Azure Application Insights. It enables advanced log filtering, container lifecycle management, and querying of cloud application traces and metrics.

Enables web performance analysis using Google PageSpeed Insights and Chrome UX Report APIs, providing compact metrics and diagnostics without local browser automation.

Enables AI assistants to connect to browser DevTools and backend debuggers for full-stack debugging, including frontend console, network, performance, and backend log analysis.

A Model Context Protocol server that provides AI assistants access to AWS CloudWatch Logs, enabling browsing, searching, summarizing, and correlating logs across multiple AWS services.

MCP server for infrastructure discovery and remote management, enabling SSH command execution, file transfer, log tailing, and machine/service inventory with a companion web dashboard.

Enables Claude Desktop to access the hosted Web Speed API through MCP, requiring only an API key for setup.