Make your Next.js site AI search ready
Next.js gives you full control over robots, metadata and rendering — which also means every gap is yours to fix. Check what AI crawlers actually receive, then wire up robots.ts, llms.txt and structured data in minutes.
Free · live crawl · includes a generated llms.txt
What Next.js gets right
- Server components and static generation put real text in the initial HTML, which is what AI crawlers read.
- app/robots.ts and app/sitemap.ts generate both files from code, so they stay in sync with your routes.
- The Metadata API makes per-page titles, descriptions and Open Graph tags straightforward.
Where Next.js sites lose AI visibility
Client-only pages
Pages marked 'use client' that fetch their content in useEffect ship an empty shell. AI crawlers don't run JavaScript, so they see nothing. Fetch on the server instead.
Preview deployments getting crawled
Indexable preview URLs can be quoted instead of your domain. Keep previews behind deployment protection or return a noindex robots.txt outside production.
Bot protection that blocks AI crawlers
Firewall or bot-management rules that challenge unknown user-agents also block GPTBot and PerplexityBot. Allow the AI crawlers you want explicitly.
No structured data
Next.js doesn't add Schema.org markup for you. Render Organization JSON-LD in the root layout and Article or Product JSON-LD on detail pages.
Real data · measured October 2026
vercel.com itself scores 81/100 B-
4 of 4 core AI crawlers allowed · publishes an llms.txt · median across the 102 sites we measured is 77. Your Next.js site starts from the same platform, but your settings and content decide the score.
Step by step
Make Next.js AI-ready
- 1
Allow AI crawlers in app/robots.ts
Generate robots.txt from code so the rules ship with every deploy.
app/robots.tsimport type { MetadataRoute } from "next"; export default function robots(): MetadataRoute.Robots { return { rules: [ { userAgent: "*", allow: "/" }, { userAgent: ["GPTBot", "OAI-SearchBot", "ChatGPT-User", "PerplexityBot", "ClaudeBot", "Claude-SearchBot", "Google-Extended"], allow: "/" }, ], sitemap: "https://yourapp.com/sitemap.xml", }; } - 2
Generate your llms.txt
Run the audit above. LLMready reads your sitemap and navigation and writes llms.txt and llms-full.txt you can drop straight into your repo.
- 3
Serve it at /llms.txt
Put the file in public/llms.txt for a static copy. To keep it current without redeploys, proxy your hosted LLMready file from a route handler instead (Pro).
app/llms.txt/route.tsexport const revalidate = 3600; export async function GET() { const res = await fetch("https://answer-engine-ready.lovable.app/h/your-site/llms.txt", { next: { revalidate: 3600 } }); return new Response(await res.text(), { headers: { "content-type": "text/plain; charset=utf-8" }, }); } - 4
Add Organization JSON-LD
Render it once in the root layout so every page tells answer engines who you are.
app/layout.tsxconst org = { "@context": "https://schema.org", "@type": "Organization", name: "Your company", url: "https://yourapp.com", logo: "https://yourapp.com/logo.png", sameAs: ["https://www.linkedin.com/company/yourcompany"], }; // inside <body> <script type="application/ld+json" dangerouslySetInnerHTML={{ __html: JSON.stringify(org) }} />