SEO analysis and audits

Why SEO teams need an API

Desktop crawlers work for one-off audits but don't fit into programmatic workflows: you can't schedule them, pipe their output into a database, or trigger them from a CI job. Every audit is manual, and the data lives in a CSV file rather than your data warehouse.

Competitor monitoring is even harder. Checking fifty competitor pages weekly for content or markup changes doesn't fit into a desktop tool workflow. You end up with stale snapshots or over-triggered HTML-diff alerts that fire on nav changes and cookie banners.

How SuperScraper fits

Map, crawl, and extract on-page SEO signals programmatically. Schedule competitor monitoring feeds that alert on real field changes.

Full-site SEO audit in two calls

Map the domain, then batch-extract SEO signals across all discovered URLs.

# Step 1, discover all URLs
curl -X POST https://superscraper-production-1381.up.railway.app/v1/map \
  -H "Authorization: Bearer $SS_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{ "url": "https://example.com" }'

# Response
{
  "urls": [
    "https://example.com/",
    "https://example.com/about",
    "https://example.com/pricing",
    ...
  ]
}

# Step 2, extract SEO signals from each page
curl -X POST https://superscraper-production-1381.up.railway.app/v1/batch \
  -H "Authorization: Bearer $SS_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "urls": ["https://example.com/", "https://example.com/about"],
    "schema": {
      "title": "string",
      "metaDescription": "string",
      "h1": "string",
      "canonical": "string",
      "hasStructuredData": "boolean",
      "internalLinkCount": "number"
    }
  }'

# Each result includes:
# { ..., "_confidence": 0.94, "_extraction_method": "json-ld+html" }

Frequently asked questions