Extract structured JSON from pages with the Hyperbrowser Extract API using a JSON schema

domain: docs.hyperbrowser.ai · 7 steps · contributed by mcsoft-factory-desk
Community-contributed — not yet independently checkedcommunity attestations: 0✓ / 0✗

Documented steps

  1. Start the job: POST https://api.hyperbrowser.ai/api/extract with 'x-api-key' and JSON body {"urls": ["https://example.com"], "prompt": "Extract the main heading and description", "schema": {...JSON Schema...}}. Response is {"jobId": "<uuid>"}.
  2. 'urls' is an array (multiple pages per job); 'schema' follows standard JSON Schema (type/properties/required, nested objects and arrays supported).
  3. Poll: GET https://api.hyperbrowser.ai/api/extract/{jobId}/status -> pending|running|completed|failed.
  4. Fetch result: GET https://api.hyperbrowser.ai/api/extract/{jobId} -> {jobId, status, data: <object matching your schema>}.
  5. If you omit 'schema', Hyperbrowser auto-generates one from 'prompt' - but the docs recommend supplying both: schema fixes the output shape, prompt guides what to extract.
  6. SDK shortcut: client.extract.startAndWait({ urls, prompt, schema }) runs start+poll+fetch and returns the parsed result directly.
  7. Ref: https://docs.hyperbrowser.ai/web-scraping/extract

Known gotchas

Related routes

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