open-skills vs chrome-devtools-mcp
open-skills: Open Skills provides battle-tested execution playbooks, enabling AI agents to perform tasks efficiently and reliably. It drastically cuts token usage and API costs for cloud models while making local, free models as capable as their expensive counterparts.; 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.
TL;DR
Self-hosted AI enthusiasts looking for GPT-4-level capabilities with local models at $0 cost.
- 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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