SEO and marketing decision
SE Ranking
Do not rebuild — SE Ranking’s proprietary multi-billion keyword and domain datasets and built-in MCP/AI skills are core, hard-to-replicate advantages; a small team can reimplement limited features but will lose the data scale and accuracy.
Visit website↗Open-source builds that already do this
Every project below is open source and already does this job today. Fork one, self-host it, or take the parts you need — the build prompt further down assumes an empty file, and this is the shortcut past that. Licences differ; check the one on each card before you ship.
What a replacement has to do
- Accept a domain or keyword list → query live SERP/keyword/backlink/audit endpoints → store results in a database → surface reports and alerts via a small web UI and simple API
What it still won’t have
- Massive proprietary data coverage (billions of keywords and domain profiles)
- Prebuilt, production-tuned data pipelines and accuracy guarantees
- MCP / built-in AI Skills and integrations to ChatGPT/Claude/etc.
- Agency-ready reporting, white-label and multi-client management out of the box
What remains hard
- Proprietary data
5.5B Keyword database
- Proprietary data
2.2B Domain profiles
- Brand trust
Trusted by 40,000+ agencies
First-year cost
Keep paying
Paying is—cheaper in year one.
On cash alone, building overtakes the subscription at 5 seats.
Money you would actually spend
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
Build a minimal self-hosted SEO data service using Python (FastAPI), Postgres, and a worker (Celery or RQ) on a single VPS. Scope: accept domains/keyword lists, schedule recurring rank/serp/backlink/audit fetch jobs (use an external SERP/backlink provider or write modular scraper adapters), store results, provide an authenticated REST API to query latest metrics and rank history, and a basic web UI (React) with a dashboard, project view, and CSV export. Out of scope: building a multi-billion keyword database, advanced ML models, white-label portal, and global RPS scaling. Include error handling, retries, rate-limit backoff, test coverage for API and worker logic, and deployment scripts (Docker Compose).
How we checked
How the score was reached
- Pay verdict base20
- An open-source build was found+5
- 4 cited sources+3
- Price verified on pricing page+3
- Hard moats found in the evidence-3
- Evidence score28
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 · 4
Every page the run actually retrieved.
- official productSE Ranking — official product
- official pricingSE Ranking API Pricing
- official docsSE Ranking Features
- open sourcetowfiqi/serpbear
Integrity checks
What held up, and what did not.
