How can I put a custom or headless website’s AI visibility content on autopilot?
Publish AI-citable content to any custom website
Create a secure HTTPS endpoint that receives an approved article tied to a monitored buyer prompt, stores it in your CMS, and exposes it as server-rendered, indexable HTML. Keep the article ID and publication URL so the same AI prompt can be measured again.
Connection method
HTTPS JSON webhook
Publishing support
Draft or published status in payload
Editorial control
Approval before delivery or in your CMS
Best fit
Headless CMSs, custom blogs, and internal pipelines
The AI visibility loop
Publishing is one controlled step in a measurable system.
- 01
Monitor buyer prompts
- 02
Find the visibility gap
- 03
Create the answer
- 04
Review evidence
- 05
Publish
- 06
Verify crawlability
- 07
Retest prompts
Copy the endpoint contract
Accept HTTPS POST requests, validate the shared secret, store by article ID, and return 2xx only after safe acceptance.
{
"payload_version": 2,
"id": "550e8400-e29b-41d4-a716-446655440000",
"created_at": "2026-05-08T10:00:00.000Z",
"published_at": "2026-05-08T10:05:00.000Z",
"title": "Example title",
"content_html": "<p>Article body</p>",
"content_markdown": "## Heading\n\nParagraph",
"content": "<p>Article body</p>",
"excerpt": "Short summary",
"slug": "example-title",
"meta_description": "Meta description for SEO",
"meta_title": "Meta title for SEO",
"tags": [
"AI visibility",
"SEO"
],
"keywords": [
"ai visibility",
"llm seo"
],
"json_ld": {
"@context": "https://schema.org",
"@type": "BlogPosting",
"headline": "Example title"
},
"status": "published",
"timestamp": "2026-05-08T10:05:00.000Z"
}Prompt an AI coding agent with the complete job
Build an authenticated, idempotent HTTPS POST endpoint for the SEOforGPT article webhook v2. Validate X-Webhook-Secret; accept payload_version, id, content_html, content_markdown, slug, meta_title, meta_description, tags, keywords, json_ld, status and timestamps; return 2xx after acceptance; and render a server-side public page with self-canonical, author, sources, internal links and sitemap inclusion.
From a real buyer question to a useful source
Example buyer prompt
“Which fraud-prevention API is best for a marketplace operating in Europe?”
What the monitoring found
Your headless site has strong documentation, but no buyer-facing decision page connecting compliance, coverage, and implementation evidence.
Own the last mile without losing the visibility context
The webhook carries structured content and metadata to your stack. Your receiving endpoint and page template are responsible for authentication, validation, idempotency, crawlability, and the final public experience.
What you need
- An HTTPS POST endpoint
- JSON parsing and validation
- A protected shared secret
- A server-rendered public article route
Set up the workflow
- 1Create the receiving endpoint.
- 2Validate the X-Webhook-Secret header.
- 3Map payload version 2 into your content model.
- 4Return a 2xx response only after successful acceptance.
- 5Send a test draft and inspect server logs.
Preserve the AI-citable article contract
The payload includes the information needed for a useful public article, but your template must render it visibly and accessibly.
- Article ID, title, HTML, and Markdown
- Slug, excerpt, meta title, and meta description
- Tags, keywords, JSON-LD, and status
- Created, published, and delivery timestamps
- Stable public route, canonical, author, sources, and internal links
AI-citable article requirements
For this page’s example buyer prompt: “Which fraud-prevention API is best for a marketplace operating in Europe?”
- Precise target question
- Focused, self-contained response
- Clear brand and product entities
- Audience and use-case context
- Verifiable first-party claims
- Relevant third-party sources
- Alternatives and comparisons
- Limitations and qualification criteria
- Descriptive headings
- Short answer-ready passages
- Useful lists or tables
- Author and update information
- Internal links and metadata
- Optional matching JSON-LD and retest date
Frequently asked questions
Clear answers about setup, publishing, and how this integration works.
Continue with the right workflow
Make
Use a Make custom webhook to receive an approved article tied to a measured buyer prompt, then route it by client, language, CMS, or publication status. Keep the source gap and final URL in the scenario so the original prompt can be tested again.
Build a visibility-to-publication scenarioZapier
Use a Zapier Catch Hook to receive an approved article created for a specific missing AI mention, map it into your CMS, notify the reviewer, and record the publication URL. The automation serves the visibility strategy; it does not choose random topics.
Build an AI visibility publishing ZapClaude
Connect Claude to live visibility data through MCP so it can identify missing brand mentions, compare competitors, inspect cited sources, and turn the best opportunity into an evidence-led content brief. Claude becomes the analysis and orchestration layer, not a generic blog writer.
Connect Claude to live AI visibility dataMeasure the answer, not the publishing volume
Start with an unanswered buyer question, publish the strongest evidence your team can stand behind, then measure whether AI mentions, position, and citations change.