"Debugging Chrome and HTML for Use with Playwright" matching MCP servers:

Enables AI to interact with Chrome DevTools Protocol to inspect and debug live web pages, including DOM, styles, console logs, and network requests.

Bridges Chrome DevTools with Cursor AI to enable debugging and monitoring, including console logs, network requests, screenshots, and element inspection.

Lets coding agents control and inspect a live Chrome browser via the Model-Context-Protocol, providing advanced browser debugging, performance insights, and reliable automation.

Enables coding agents to control and inspect a live Chrome browser for reliable automation, in-depth debugging, and performance analysis via Chrome DevTools.

Lets coding agents control and inspect a live Chrome browser for reliable automation, in-depth debugging, and performance analysis. Provides access to Chrome DevTools capabilities such as tracing, network inspection, screenshots, and console messages through MCP clients.

Lets AI coding assistants control and inspect a live Chrome browser using full Chrome DevTools capabilities for browser automation, debugging, and performance analysis.

An MCP server that lets AI coding agents control and inspect a live Chrome browser, providing reliable automation, debugging, and performance analysis through Chrome DevTools.

Enables AI coding agents to control and inspect a live Chrome browser, providing reliable automation, in-depth debugging, and performance analysis through Chrome DevTools.

A minimal network monitoring MCP tool for Playwright browser automation. Just 5 simple tools to capture, filter, and analyze network traffic during web automation with MCP context efficiency.

A Model Context Protocol (MCP) server for Chrome Enterprise Premium that exposes DLP rules, content detectors, connector policies, browser telemetry, and license management as MCP tools, enabling any MCP-compatible AI agent to inspect and configure a Chrome Enterprise environment.

A server that analyzes website performance using Playwright and Lighthouse, allowing LLMs to perform web performance analysis through the Model Context Protocol.

Enables debugging of web applications by connecting Claude to Chrome's developer tools through MCP, allowing network monitoring, console inspection, and performance analysis via natural language.

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.

Enables querying real-user Core Web Vitals field measurements — 75th-percentile LCP, INP, and CLS with distributions and ~40 weeks of history — for any origin or page that has enough Chrome traffic.

Enables tracing mcp-use tool callbacks and capturing tool errors and exceptions in Sentry via MCP middleware, without SDK changes or additional services.

Captures browser console logs via Chrome DevTools Protocol and exposes them to MCP clients over SSE, enabling log retrieval with the getConsoleLogs tool.

Enables LLMs to interact with Kibana through composable toolboxes for building dashboards, managing data, and handling alerts, among other operations.

An unofficial MCP server that connects AI assistants to Akamai APIs, providing tools for edge diagnostics, debugging, and network analysis.

Enables AI agents to interact seamlessly with Splunk environments through 20+ tools for search, analytics, data discovery, administration, and health monitoring. Features AI-powered troubleshooting workflows and supports multiple Splunk instances with production-ready security.

Enables interaction with Google Cloud services including billing cost analysis, log querying, and metrics monitoring through natural language commands. Provides comprehensive tools for managing GCP resources, analyzing costs, detecting anomalies, and retrieving operational insights.