curl "https://api.dashify.aurbyn.com/api/v1/blogs?limit=5&fields=summary" \
  -H "x-api-key: nbl_your_key"

GET /api/v1/store HTTP/1.1
Host: api.dashify.aurbyn.com
x-api-key: nbl_your_key

{ "success": true, "data": { … }, "pagination": { "page": 1, "limit": 50, "total": 24, "pages": 1 } }

{ "success": false, "message": "Invalid API key" }

---
title: "How to track ChatGPT traffic to your website"
slug: "how-to-track-chatgpt-traffic"
metaTitle: "How to track ChatGPT traffic to your website"
metaDescription: "What assistant referrers look like and which tools show them as their own channel."
excerpt: "You can see ChatGPT traffic by grouping referrers from chatgpt.com into their own channel."
author: "Clerion Research Team"
category: "AI traffic"
tags: ["ai traffic", "chatgpt"]
image: "https://i.ibb.co/…/cover.png"
imageAlt: "A referrer table with assistant domains grouped"
targetKeyword: "track ChatGPT traffic"
---

## Why it matters

Assistant referrals are a growing channel…

## Frequently asked questions

### Does ChatGPT send a referrer?

Yes, in most browsers links clicked inside ChatGPT carry chatgpt.com as the referrer.

## Sources

- [OpenAI crawler documentation](https://platform.openai.com/docs/bots)

// app/blog/[slug]/page.tsx
const API = "https://api.dashify.aurbyn.com/api/v1";
const headers = { "x-api-key": process.env.NEBULAR_API_KEY! };

export async function generateMetadata({ params }) {
  const { data } = await fetch(`${API}/blogs/slug/${params.slug}`, { headers, next: { revalidate: 300 } }).then((r) => r.json());
  return {
    title: data.seo.metaTitle,
    description: data.seo.metaDescription,
    alternates: { canonical: `/blog/${data.slug}` },
    openGraph: data.seo.openGraph,
    twitter: data.seo.twitter,
  };
}

export default async function Post({ params }) {
  const { data } = await fetch(`${API}/blogs/slug/${params.slug}`, { headers, next: { revalidate: 300 } }).then((r) => r.json());
  return (
    <article>
      <script type="application/ld+json" dangerouslySetInnerHTML={{ __html: JSON.stringify(data.jsonLd) }} />
      <h1>{data.title}</h1>
      <p className="excerpt">{data.seo.excerpt}</p>
      <div dangerouslySetInnerHTML={{ __html: data.content }} />
    </article>
  );
}

// app/llms.txt/route.ts
export async function GET() {
  const text = await fetch(`${API}/blogs/llms.txt`, { headers, next: { revalidate: 300 } }).then((r) => r.text());
  return new Response(text, { headers: { "content-type": "text/plain; charset=utf-8" } });
}

Integrate the Nebular public API into Next.js. Produce production-ready code.

## API
Base URL: https://api.dashify.aurbyn.com/api/v1
Auth: header x-api-key: <key> (keys start with nbl_). Keep the key server-side or in an environment variable.
Every response: { success: boolean, data: any, message?: string }. Errors: 401 bad key, 403 domain not verified, 404 not found, 429 rate limit (100 requests/minute per IP), 500 server error.

## Endpoints to use
### Blog with SEO
- GET /blogs?fields=summary → items carry slug, url, excerpt, metaTitle, metaDescription, category, publishedAt, updatedAt, readingTimeMinutes
- GET /blogs/slug/:slug → post + seo { metaTitle, metaDescription, excerpt, toc, faqs, sources, openGraph, twitter, jsonLd } + markdown
- Feeds to proxy: GET /blogs/llms.txt, /blogs/llms-full.txt, /blogs/rss.xml, /blogs/sitemap.xml
- Render seo.metaTitle/metaDescription in <head>, embed jsonLd as application/ld+json, print seo.excerpt under the H1.

## Requirements
- Handle loading, empty and error states.
- Cache reads for a few minutes where the framework allows.
- For blog pages, use the seo block for <head> tags and embed jsonLd; never recompute what the API already derives.
- Comment each API call briefly.