Short answer: You can extract structured data in Firecrawl by hand from its own interface, but it won’t repeat itself. On TinyCommand, add the Firecrawl Extract Structured Data action to a workflow, map its 4 inputs from any upstream app, and it runs automatically every time the trigger fires. No code, and a free tier to start.
Every field can be mapped from an upstream trigger, AI step, table row, or hard-coded literal.
| Field | Type | Required | Description |
|---|---|---|---|
URL url | string | Required | Fully-qualified URL of the page to extract from. |
Extraction Prompt prompt | string | Optional | Optional natural-language description of what to extract. Either Prompt or Schema (or both) must be set — Prompt alone lets the model pick the shape; Schema alone gives strict structure; together is most reliable. |
Output Schema schema | json_schema | Optional | Optional JSON Schema describing the desired output shape. Define properties + types row-by-row. Either Schema or Prompt (or both) must be set. |
Only Main Content only_main_content | boolean | Optional | Strip navigation/footer/sidebar boilerplate before extraction. Almost always true — cleaner extraction, fewer tokens, lower cost. |
{"url": "e.g. https://news.ycombinator.com","prompt": "e.g. Extract the product name, price (number), and short description.","schema": "{{trigger.schema}}","only_main_content": "{{trigger.only_main_content}}"}
{"data": {"json": {"title": "I Moved My Digital Stack to Europe","points": 271},"metadata": {"sourceURL": "https://news.ycombinator.com"}},"success": true}
Use these fields in downstream nodes for routing, logging, or error handling.
Any of these apps can fire this action as part of a workflow.