Chrome DevTools 141 update with AI integration for devs

AI agents used to code like they were blindfolded.  They’d write JavaScript, cross their fingers, and hope it worked.   No browser. No feedback. Just vibes. But now?   Google gave them 𝐞𝐲𝐞𝐬. 𝐂𝐡𝐫𝐨𝐦𝐞 𝐃𝐞𝐯𝐓𝐨𝐨𝐥𝐬 𝐌𝐂𝐏 lets your AI actually open a browser, click buttons, read the DOM, check console logs, and even run performance audits. It’s like giving your AI a front-row seat to the app it’s building. Imagine this:   → Your agent writes code   → Launches Chrome   → Clicks through the UI   → Finds the bug   → Fixes it   → And tells you what it did No more “looks good in theory.”   Now it 𝐬𝐞𝐞𝐬 what’s broken, and fixes it like a real dev. This changes everything for agentic workflows.  From debugging to performance tuning to full-on QA testing, your AI can now 𝐢𝐧𝐭𝐞𝐫𝐚𝐜𝐭 with the web, not just imagine it. We’re not just building tools anymore.   We’re building teammates. #AgenticAI #ChromeDevToolsMCP #BuildInPublic #AIWorkflows #DevTools #AddyOsmani #TechHumor   Read the full breakdown (https://lnkd.in/dT2Dh_AN)

<<Chrome DevTools MCP,” a Model Context Protocol (MCP) server that lets AI coding agents control and inspect a real Chrome instance—recording performance traces, inspecting the DOM and CSS, executing JavaScript, reading console output, and automating user flows. The launch directly targets a well-known limitation in code-generating agents: they usually cannot observe the runtime behavior of the pages they create or modify. By wiring agents into Chrome’s DevTools via MCP, Google is turning static suggestion engines into loop-closed debuggers that run measurements in the browser before proposing fixes. What exactly is Chrome DevTools MCP? MCP is an open protocol for connecting LLMs to tools and data. Google’s DevTools MCP acts as a specialized server that exposes Chrome’s debugging surface to MCP-compatible clients. Google’s developer blog positions this as “bringing the power of Chrome DevTools to AI coding assistants,” with concrete workflows like initiating a performance trace (e.g., performance_start_trace) against a target URL, then having the agent analyze the resulting trace to suggest optimizations (for example, diagnosing high Largest Contentful Paint). >>

Have you tried the Chrome DevTools #MCP server? Chrome has just given #AI coding assistants the ability to see what they build. This is the future of web development - where AI doesn't just write code, but can verify, debug, and optimize it in real-time. I'd love to hear your experience! This is the future of web development, and it's happening now! 🚀 **What You Can Do Now:** Verify Code Changes in Real-Time: "Verify in the browser that your change works as expected." Diagnose Network and Console Errors: "A few images on localhost:8080 are not loading. What's happening?" Simulate User Behavior: "Why does submitting the form fail after entering an email address?" Debug Live Styling Issues: "The page on localhost:8080 looks strange and off. Check what's happening there." Automate Performance Audits: "Localhost:8080 is loading slowly. Make it load faster." **The Technical Magic:** The Chrome DevTools MCP server provides tools like `performance_start_trace` that allow LLMs to start Chrome, open websites, and use DevTools to record performance traces. The AI can then analyze these traces to suggest concrete improvements. **Why This Matters:** This isn't just about debugging - it's about **transforming how we build web applications**. AI assistants can now: - See the real impact of their code changes - Verify solutions work as intended - Catch issues before they reach production - Provide data-driven optimization suggestions --- #WebDevelopment #ChromeDevTools #MCP #DeveloperProductivity #AI #Debugging #TechInnovation #WebDev #Automation #Building #QualityAssurance #Chrome #CodingAssistants

𝗬𝗼𝘂𝗿 𝗔𝗜 𝗖𝗼𝗱𝗶𝗻𝗴 𝗔𝘀𝘀𝗶𝘀𝘁𝗮𝗻𝘁 𝗶𝘀 𝗡𝗼 𝗟𝗼𝗻𝗴𝗲𝗿 𝗕𝗹𝗶𝗻𝗱 The biggest bottleneck with AI code generation? The agent is blind. It writes code for your web application, but has no way of knowing if it actually works, looks right, or performs well in a browser. This leaves you to manually copy, paste, test, and debug everything it produces. Until now. 𝗖𝗵𝗿𝗼𝗺𝗲 𝗗𝗲𝘃𝗧𝗼𝗼𝗹𝘀 𝗠𝗖𝗣 is a game-changer, acting as the eyes and hands for your AI agent inside the browser. It gives coding assistants direct access to a live Chrome instance to analyze performance, inspect the DOM, and debug issues in real-time. What this means for developers: ✅ 𝗙𝗮𝘀𝘁𝗲𝗿 𝗗𝗲𝘃𝗲𝗹𝗼𝗽𝗺𝗲𝗻𝘁: Let your AI generate and self-correct UI components on the fly. ✅ 𝗙𝗲𝘄𝗲𝗿 𝗕𝘂𝗴𝘀: The agent can spot console errors and visual glitches before they ever get to you. ✅ 𝗥𝗲𝗹𝗶𝗮𝗯𝗹𝗲 𝗔𝘂𝘁𝗼𝗺𝗮𝘁𝗶𝗼𝗻: It uses Puppeteer to ensure tests run smoothly without manual intervention. It's already compatible with popular tools like Cursor, Claude Code, and the Gemini CLI. The gap between an idea and a working, tested UI just got incredibly small. Best of all, it's completely open source. Explore the project on GitHub and see how it works: https://lnkd.in/gBtmGvbV What's the first tedious frontend task you would automate with this? #FrontendDevelopment #AI #GenAI #DeveloperTools #Tech #OpenSource #ChromeDevTools

Chrome DevTools MCP: Giving AI Assistants (Proper) Eyes Into Your Browser As AI becomes more ingrained in software development, our workflow needs to evolve. Code generation without context is already hitting diminishing returns. But with tools like Chrome DevTools MCP, AI can debug, observe, verify, and adjust, all within the browser. That’s not just convenience, it’s a paradigm shift for how we build, test, and maintain web applications. Chrome DevTools MCP brings: catching layout issues, diagnosing console errors, measuring Core Web Vitals, iterating on fixes: without going back and forth endlessly. It's different and more powerful then Playwright MCP. Read more here: https://lnkd.in/day5rTtq #google #chrome #mcp #devtools #ai

Developers, you're sleeping on this! 🚀 Chrome DevTools MCP Just Changed the Game For years, AI coding assistants could only generate code. Now, with Google Chrome DevTools MCP, they can finally see what that code does. This new protocol bridges AI directly to a live browser giving agents real access to; the DOM, console errors, network requests & performance traces That means your AI assistant can now run your app, debug it, spot layout shifts, trace API calls, and tell you why something’s broken - not just guess. This is a massive shift. For the first time, AI can reason about live runtime behaviour, not just static text. The line between developer and debugger just blurred. We’re entering an era where AI doesn’t just write your front end! It tests, validates, and optimizes it in real time. And it all starts with Chrome DevTools MCP. https://lnkd.in/d3_92Jn7

Ever built a web app by pure vibe—prompting AI to spit out code, then crossing your fingers for a flawless refresh? 🚀 That's the thrill of Vibe Coding... until bugs ambush you in the shadows, and debugging devours your day. But what if your AI sidekick could actually see the runtime? Enter Chrome DevTools MCP: the open-source bridge turning GitHub Copilot into a browser-peering detective. In my hands-on week with a Next.js e-commerce dashboard, it slashed bugs by 70%, doubled my feature output, and made "intent-driven dev" verifiable—not a gamble. Here's the glow-up: 𝐅𝐫𝐨𝐦 𝐂𝐡𝐚𝐨𝐬 𝐭𝐨 𝐂𝐥𝐚𝐫𝐢𝐭𝐲: Prompt a responsive grid? MCP captured screenshots, DOM snapshots, and console ghosts—fixing mobile overflows in under 5 mins. No more tab-juggling. 𝐑𝐮𝐧𝐭𝐢𝐦𝐞 𝐒𝐮𝐩𝐞𝐫𝐩𝐨𝐰𝐞𝐫𝐬: Simulated slow 3G for perf tweaks (hello, 2-sec load cuts via WebP swaps) and nabbed silent CORS errors before they bit. 𝐀𝐠𝐞𝐧𝐭𝐢𝐜 𝐌𝐚𝐠𝐢𝐜: Tools like click, emulate_network, and evaluate_script let Copilot self-heal race conditions—evolving vibes into bulletproof code. Launched by Anthropic in '24, MCP is the "USB-C for AI agents," wrapping Chrome's DevTools into seamless loops: generate → observe → refine. It cured my Vibe Coding hangover, grounding hallucinations in live data without killing the creative buzz. The result? Ship faster, safer, and smarter. Who's ready to director your AI instead of babysitting it? What's your wildest Vibe Coding win (or wipeout)? Tried MCP yet? Read the full article here : https://lnkd.in/gKTG3Q-X This post reflects my personal views and not those of my organisation. #VibeCoding #AICoding #ChromeDevTools #AgenticDevelopment #AI #SLIThoughtLeadership

A Step-by-Step Guide to Chrome DevTools MCP for AI Assistants Hey everyone! I’m excited to share something that’s a real game-changer for anyone who writes code for the web. I’m talking about the new Chrome DevTools Model Context Protocol (MCP) server. If you want to know more details, read the article until the end. AI coding assistants are great at generating code. They can write the code, but they can’t see what it actually does when it runs in a browser. This means a lot of guesswork and back-and-forth for developers. But that’s all about to change. The Chrome DevTools MCP server enables an AI agent to debug web pages directly in Chrome, utilizing the same powerful DevTools. This means an AI assistant can now identify and fix issues with much greater accuracy. The Chrome DevTools MCP server is a specific implementation of the Model Context Protocol (MCP) that adds debugging capabilities to an AI agent. With this new tool, my AI assistant can: Verify code changes in real-time: It can generate a fix and then automatically check if it works as https://lnkd.in/gy6-wDrV

A Step-by-Step Guide to Chrome DevTools MCP for AI Assistants Hey everyone! I’m excited to share something that’s a real game-changer for anyone who writes code for the web. I’m talking about the new Chrome DevTools Model Context Protocol (MCP) server. If you want to know more details, read the article until the end. AI coding assistants are great at generating code. They can write the code, but they can’t see what it actually does when it runs in a browser. This means a lot of guesswork and back-and-forth for developers. But that’s all about to change. The Chrome DevTools MCP server enables an AI agent to debug web pages directly in Chrome, utilizing the same powerful DevTools. This means an AI assistant can now identify and fix issues with much greater accuracy. The Chrome DevTools MCP server is a specific implementation of the Model Context Protocol (MCP) that adds debugging capabilities to an AI agent. With this new tool, my AI assistant can: Verify code changes in real-time: It can generate a fix and then automatically check if it works as https://lnkd.in/gy6-wDrV

A Step-by-Step Guide to Chrome DevTools MCP for AI Assistants Hey everyone! I’m excited to share something that’s a real game-changer for anyone who writes code for the web. I’m talking about the new Chrome DevTools Model Context Protocol (MCP) server. If you want to know more details, read the article until the end. AI coding assistants are great at generating code. They can write the code, but they can’t see what it actually does when it runs in a browser. This means a lot of guesswork and back-and-forth for developers. But that’s all about to change. The Chrome DevTools MCP server enables an AI agent to debug web pages directly in Chrome, utilizing the same powerful DevTools. This means an AI assistant can now identify and fix issues with much greater accuracy. The Chrome DevTools MCP server is a specific implementation of the Model Context Protocol (MCP) that adds debugging capabilities to an AI agent. With this new tool, my AI assistant can: Verify code changes in real-time: It can generate a fix and then automatically check if it works as https://lnkd.in/gy6-wDrV