chrome-devtools-mcp vs kernel-mcp-server
chrome-devtools-mcp: chrome-devtools-mcp enables AI coding assistants like Gemini, Claude, and Copilot to interact with a live Chrome browser via the Model-Context-Protocol (MCP). It grants AI full access to Chrome DevTools for reliable automation, deep debugging, and detailed performance insights.; kernel-mcp-server: Kernel MCP Server bridges AI assistants with the Kernel platform, enabling deployment of apps, headless Chromium browser automation, monitoring, and more. It supports OAuth 2.0 authentication and is fully managed with an open-source codebase. Users can use the cloud-hosted endpoint or run locally.
TL;DR
- You want an agent to record a Chrome performance trace and get insights from it; the README lists performance_start_trace, performance_stop_trace and performance_analyze_insight.
- You need to inspect network requests, console messages and screenshots of a page while debugging it.
- You want the agent to attach to a Chrome you already have running, using --browser-url, --ws-endpoint or --autoConnect (Chrome 144+).
- You need Firefox or Safari: the project is built on Chrome DevTools and targets Chrome.
- You want a general-purpose automation or test runner across browsers; Playwright MCP is the closer fit.
- You cannot run Node.js 20.19 or newer, which the README lists as a requirement.
AI coding workflows: preview local changes in a cloud browser via tunnel
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