Extract PDF Tables via OCR.space + n8n Webhook to Google Sheets

Extract tables from any PDF URL and push the results to Google Sheets—automatically with OCR.space + n8n

This n8n workflow receives a public PDF URL via webhook, runs OCR.space with table detection, converts the extracted content into best-effort rows and CSV, and (optionally) appends the data to Google Sheets. It then returns the extracted text, rows, and CSV back in the webhook response.

What this workflow does

• Webhook input: Accepts a POST request containing JSON like {"pdfUrl":"https://..."}.
• OCR + table detection: Sends the PDF URL to the OCR.space API and uses the returned ParsedResults[].ParsedText.
• Text cleanup & row derivation: Cleans the extracted text into plain text lines and derives table-like rows by splitting on tabs or repeated whitespace.
• CSV + structured output: Builds a CSV representation of the detected rows and responds with JSON containing the full extracted text, rows, and CSV.
• Optional Google Sheets append: If configured, appends extracted fields to a target worksheet using Google Sheets OAuth2.

Use cases

• Turn PDF reports, statements, or exported documents with tabular data into spreadsheets for faster analysis.
• Automate data extraction pipelines when you have PDFs available via public URLs.
• Collect OCR results for QA review by storing the parsed rows and original extracted text.

Technical details

• n8n nodes: Code, Webhook, HTTP Request, Google Sheets, Respond to Webhook.
• OCR provider: OCR.space using the OCR_SPACE_API_KEY environment variable.
• Webhook response: Returns structured JSON with extracted text plus rows/CSV.

Tip: Use the production webhook URL from n8n and ensure the PDF is publicly reachable.