SEO and marketing decision

VibeSEO

A competent developer can build a one-site MVP (crawl, keyword discovery, LLM drafts, approval UI, publish connector) in about a week and maintain it; the vendor's directory integrations and backlink/history features are conveniences rather than insurmountable moats.

Visit website
You pay

$9/mo

$108/yr

Read off the official pricing page.

You’d pay instead

$100one-off38 h to build

$100/mo6 h/mo upkeep

On cash alone, building overtakes the subscription at 13 seats.

No open-source build does this yet

Nothing published replaces this one, so a replacement starts from an empty file. Here is what it would have to cover.

What a replacement has to do

  • Crawl a site for context, discover keywords and topics, generate SEO-first article drafts with an LLM, show an approval UI, and publish approved HTML to the target site; track impressions via Search Console.

What it still won’t have

  • Official one-click ChatGPT app integration (listed as "Official ChatGPT app").
  • Official Claude connector with OAuth and live connector directory entry.
  • Backlink profile & history features (backlink lookups billed via credits).
  • Hosted credits model and bundled crawler (VibeSEObot) and the vendor-managed publishing flow.

What remains hard

  • Product polish and ongoing maintenance
Read the build prompt

First-year cost

Keep paying

Paying is—cheaper in year one.

On cash alone, building overtakes the subscription at 13 seats.

Paid seatsseats

Money you would actually spend

Keep paying
—

Subscription price × seats × 12

Build it
—

AI build —APIs + hosting —

Time you would spend

—

—

What you would spend

What we assumed

The verdict above measures whether you could build it. This one is only about money.

Runnable build prompt

Not run yet
Build a minimal AI-driven SEO autopilot using Next.js (React) frontend, Node/Express API, Postgres for state, and a small worker (BullMQ) for scheduled crawling and publishing. Core features in scope: (1) site crawler that extracts pages and metadata, (2) keyword/topic discovery using a keyword-data API or SERP scraping component, (3) LLM draft generator endpoint (OpenAI API) that returns title, meta, headings, FAQ, internal links and JSON-LD, (4) approval dashboard to preview drafts and trigger publish, (5) WordPress and static-site publish adapters (OAuth/API + Git-based publish), (6) Search Console integration to import impressions/queries and a simple dashboard. Out of scope: multi-tenant billing, backlink historical visualizations, ChatGPT/Claude app directory packaging. Provide logging, error handling, unit tests for API endpoints, end-to-end tests for the publish flow, and deployment scripts for a single VPS or managed platform (Render/Vercel + Heroku/Managed Postgres).
How we checked2 sources · 2/3 runs agreed · evidence score 82

How the score was reached

  • Build verdict base78
  • 2 cited sources+1
  • Price verified on pricing page+3
  • Evidence score82

The base comes from the verdict. Everything under it is a check that either happened or did not, and each one is a fact frozen in this record rather than a judgement made at render time - so the same evidence always produces the same number.

How scoring works →

Cited sources · 2

Every page the run actually retrieved.

Integrity checks

What held up, and what did not.

✓ Price read off the page! 2 of 3 runs agreed; the verdict is the majority✓ Citations limited to fetched pages! 1 moat recorded