Agent Lighthouse MCP Server
⚡ 快速开始
直接在终端中运行零安装扫描。--view 标志会打开独立的 HTML 报告,用于截图、利益相关者审查和拉取请求工件。
# 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 Lighthouse 检查 199 条规则,涵盖 llms.txt、robots.txt 爬虫策略、Schema.org、OpenAPI 发现、WebMCP 操作面、AEO/GEO 内容结构、可访问性和技术准备度。
Related MCP server: Seonix SEO MCP
🎯 Agent Lighthouse 检查内容
Agent Lighthouse 评估网站的 10 个审计类别,分为 3 个准备度支柱:
├── 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)📦 包与架构
本仓库组织为轻量级 pnpm 单体仓库,发布在 @forkpoint 作用域下:
包 | npm 包 | 描述 |
| 主 CLI 二进制文件( | |
| 核心收集器-审计引擎、评分算法和类型。 | |
| 独立 HTML、Markdown 和统一报告视图模型。 | |
| 用于 Claude / Cursor / IDE 的模型上下文协议(MCP)服务器。 |
🛡️ GitHub Actions CI
将 Agent Lighthouse 用作拉取请求门控,以检测智能体准备度的回归:
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 }}该操作会生成终端、HTML、JSON 和 Markdown 报告。设置 comment-on-pr: true 并配合 github-token,可在拉取请求上发布 Markdown 摘要。请参阅市场设置指南获取发布就绪的示例。
💻 程序化 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);🤖 模型上下文协议(MCP)服务器
将 Agent Lighthouse 添加到你的 Claude Desktop 或 Cursor IDE,让 AI 编码智能体审计实时暂存 URL:
{
"mcpServers": {
"agent-lighthouse": {
"command": "npx",
"args": ["-y", "@forkpoint/agent-lighthouse-mcp"]
}
}
}📣 分享你的评分
生成的报告是独立文件,团队可以将其附加到拉取请求、发送给客户或发布改进前后的对比。
[](https://github.com/ForkPoint/agent-lighthouse)如果你在公共站点上运行 Agent Lighthouse,请通过站点评分模板分享结果。好的示例有助于其他开发者了解智能体就绪的站点是什么样的。
更多发布材料位于:
🛠️ 开发
# 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📄 许可证
GPL-3.0-only © ForkPoint
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