Agent Lighthouse MCP Server
⚡ 빠른 시작
터미널에서 설치 없이 바로 스캔을 실행하세요. --view 플래그를 사용하면 독립 실행형 HTML 보고서가 열리며, 스크린샷, 이해관계자 검토, 풀 리퀘스트 아티팩트에 활용할 수 있습니다.
# Instant audit (prints terminal report & generates HTML + JSON reports)
npx @forkpoint/agent-lighthouse https://yourstore.com
# Open the standalone HTML report in your browser
npx @forkpoint/agent-lighthouse https://yourstore.com --view
# Run in CI and fail if score is below threshold
npx @forkpoint/agent-lighthouse https://staging.yourstore.com --min-score 85Agent Lighthouse는 llms.txt, robots.txt 크롤러 정책, Schema.org, OpenAPI 검색, WebMCP 액션 표면, AEO/GEO 콘텐츠 구조, 접근성, 기술 준비 상태를 포함한 199개 규칙을 확인합니다.
Related MCP server: Seonix SEO MCP
🎯 Agent Lighthouse가 확인하는 항목
Agent Lighthouse는 3가지 준비 기둥으로 그룹화된 10개 감사 카테고리에 걸쳐 웹사이트를 평가합니다:
├── 1. Agentic Readiness
│ ├── AI Agent Tools & Action Surfaces (WebMCP manifests, OpenAPI specs, agents.json, ai-plugin.json)
│ ├── Content Discoverability (llms.txt, llms-full.txt, sitemaps, commerce links)
│ └── AI Crawler Permissions (robots.txt rules for GPTBot, ClaudeBot, PerplexityBot, etc.)
│
├── 2. AI Search Optimization
│ ├── Answer Engine Optimization (AEO) (direct answerability, step lists, table schemas)
│ └── Generative Engine Optimization (GEO) (unique data density, authoritative citations)
│
└── 3. Technical Foundation
├── Structured Data & Schema Markup (Schema.org Product, Offer, SKU, GTIN, Organization)
├── Meta Tags & AI Head Elements (AI content declarations, canonicals, Open Graph)
├── Semantic HTML & Content Structure (Headings hierarchy, landmarks, semantic tags)
├── Accessibility & Agent Interaction (Form labels, button roles, interactable elements)
└── Technical Readiness & Security (HTTPS, security.txt, TTFB response latency)📦 패키지 및 아키텍처
이 저장소는 @forkpoint 범위로 게시된 경량 pnpm 모노레포로 구성되어 있습니다:
패키지 | npm 패키지 | 설명 |
| 주요 CLI 바이너리 ( | |
| 핵심 수집기-감사 엔진, 점수 알고리즘 및 타입. | |
| 독립 실행형 HTML, Markdown 및 통합 보고서 뷰 모델. | |
| Claude / Cursor / IDE용 Model Context Protocol (MCP) 서버. |
🛡️ GitHub Actions CI
에이전트 준비 상태 회귀를 위한 풀 리퀘스트 게이트로 Agent Lighthouse를 사용하세요:
name: Agent Lighthouse
on:
pull_request:
branches: [main]
jobs:
agent-lighthouse:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- uses: ForkPoint/agent-lighthouse@main
with:
url: https://staging.yourstore.com
preset: ecommerce
min-score: "85"
github-token: ${{ secrets.GITHUB_TOKEN }}이 액션은 터미널, HTML, JSON 및 Markdown 보고서를 생성합니다. comment-on-pr: true와 github-token을 설정하면 풀 리퀘스트에 Markdown 요약을 게시합니다. 릴리스 준비 예제는 마켓플레이스 설정 가이드를 참조하세요.
💻 프로그래밍 방식 Node.js / TypeScript SDK
import { runScan } from "@forkpoint/agent-lighthouse-core";
import {
buildReportView,
generateHtmlReport,
} from "@forkpoint/agent-lighthouse-report";
const report = await runScan("https://example.com");
const view = buildReportView(report);
console.log(`Overall Score: ${view.overallScore}/100 (${view.scoreTier})`);
// Generate standalone HTML report
const html = generateHtmlReport(report);🤖 Model Context Protocol (MCP) 서버
Claude Desktop 또는 Cursor IDE에 Agent Lighthouse를 추가하여 AI 코딩 에이전트가 라이브 스테이징 URL을 감사하도록 하세요:
{
"mcpServers": {
"agent-lighthouse": {
"command": "npx",
"args": ["-y", "@forkpoint/agent-lighthouse-mcp"]
}
}
}📣 점수 공유
생성된 보고서는 독립 실행형 파일이므로, 팀에서 풀 리퀘스트에 첨부하거나, 클라이언트에 보내거나, 개선 전후를 게시할 수 있습니다.
[](https://github.com/ForkPoint/agent-lighthouse)공개 사이트에서 Agent Lighthouse를 실행했다면, 사이트 점수 템플릿을 통해 결과를 공유해 주세요. 좋은 예시는 다른 개발자들이 에이전트 준비 사이트가 어떤 모습인지 배우는 데 도움이 됩니다.
더 많은 출시 자료는 다음에서 확인할 수 있습니다:
🛠️ 개발
# Clone the repository
git clone https://github.com/ForkPoint/agent-lighthouse.git
cd agent-lighthouse
# Install dependencies
pnpm install
# Build all packages
pnpm build
# Run unit tests
pnpm test📄 라이선스
GPL-3.0-only © ForkPoint
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