"browser" matching MCP servers:

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

An MCP server that provides AI coding assistants with comprehensive browser automation and debugging capabilities using Playwright, including visual inspection, DOM debugging, and execution monitoring.

A Docker-based workspace providing headless Chrome browser with CDP proxy and noVNC interface for browser automation and monitoring.

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.

Enables coding agents to access local browser diagnostics—runtime errors, console logs, network failures, breadcrumbs, DOM snapshots, and screenshots—and run closed-loop verification to debug and confirm fixes.

Enables AI assistants to search, summarize, and inspect Kibana/OpenSearch Dashboards logs through the user's logged-in browser session, eliminating the need for API keys or service accounts.

AI-powered QA testing platform — catches JS errors, accessibility failures, visual regressions, API loops, security issues, and more via Chrome DevTools MCP

Pull open jobs from Workday, Greenhouse, Lever and Ashby career sites as normalized JSON with one tool call. Change tracking returns only jobs added, edited or closed since the previous run. Calls the hosted Apify Actor: set APIFY_TOKEN; tool calls are billed pay-per-event on Apify. No browser, login or proxy.

Enables MCP-compatible agents to run real browser-based performance scans on any URL and receive a rich Markdown dashboard with Core Web Vitals, grades, and actionable recommendations.

Lets AI assistants query Dynatrace Managed environments — services, traces, metrics, pods, and problems — by running read-only GET requests through your already logged-in browser session, so no API tokens are needed. All traffic stays on your machine between the AI client, a local server, and a browser extension.

Enables Claude Code to inspect live browser-preview state, including forms, routes, selections, and focus, and to access runtime errors and user interaction events from any browser tab via read-only MCP tools.

Connects AI assistants to Crontinel, enabling natural language queries about cron jobs, queues, Horizon status, and alerts without opening a browser.

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.

Enables AI coding agents to observe real-time Node, Vite, Next.js, Storybook, TypeScript, and browser runtime errors from a wrapped dev server, source-mapped to exact file, line, and column with the log lines preceding each crash. It exposes MCP tools for listing open errors, fetching full stack details, and checking or marking fixes as resolved, all locally with no code changes.

Point your coding agent at a URL and get a real-browser QA audit: broken signup/login/checkout flows, JS console errors, missing analytics, consent + security headers, mobile tap targets, and accessibility — returned as machine-verified findings graded A-F.

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 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.

Enables agents to inspect BOINC Central batch status, review job details, and download or extract batch output without a browser, including for BUDA Docker batches and other remote-submission apps. It also supports aborting or retiring batches with explicit confirmation.

Connects AI coding clients to a running Flutter app's Dart VM Service so they can stream live exceptions with stack traces, logs, network calls, frame timings, memory, rebuild attribution and navigation state as structured tool results. It also correlates that evidence into root-cause diagnoses with confidence and suggested fixes, and streams everything to a browser dashboard.