chrome-devtools-mcp vs hanzi-browse
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.; hanzi-browse: Hanzi Browse provides 24 site playbooks as hints for LLM-based browsing agents, helping them handle complex real-world websites. It offers two modes: as a browser sub-agent for coding agents or as a REST API/SDK for product integration. The tool automatically configures MCP for multiple AI agents and requires only an npx command to set up.
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.
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Side-by-Side Comparison
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