No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by danielsogl · MCP Server · ★ 71
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is lighthouse-mcp-server safe to install? View the security audit →
Lighthouse MCP Server A Model Context Protocol (MCP) server that provides comprehensive web performance auditing and analysis capabilities using Google Lighthouse. This server enables LLMs and AI agents to perform detailed website performance assessments, accessibility audits, SEO analysis, security checks, and Core Web Vitals monitoring. 🌟 Key Features 🚀 Performance Analysis: Complete Lighthouse audits with Core
| Stars | 71 |
| Forks | 13 |
| Language | TypeScript |
| Category | MCP Server |
| License | MIT |
| Quality Score | 69.8705588825353/100 |
| Open Issues | 7 |
| Last Updated | 2026-09-21 |
| Created | 2025-06-01 |
| Platforms | browser, mcp, node |
| Est. Tokens | ~19k |
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lighthouse-mcp-server is MCP server that enables AI agents to perform comprehensive web audits using Google Lighthouse with 13+ tools for performance, accessibility, SEO, and security analysis.. It is categorized as a MCP Server with 71 GitHub stars.
lighthouse-mcp-server is primarily written in TypeScript. It covers topics such as lighthouse, lighthouse-audits, lighthouse-score.
You can find installation instructions and usage details in the lighthouse-mcp-server GitHub repository at github.com/danielsogl/lighthouse-mcp-server. The project has 71 stars and 13 forks, indicating an active community.
lighthouse-mcp-server is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to lighthouse-mcp-server on Agent Skills Hub include pagespeed-insights-mcp, ultraship, lighthouse-mcp. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. It is a first-layer scan, not a manual audit — we say so rather than overstate it.
The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.
Sources & who's responsible: