PDF Table Extractor (x402) is a paid API for AI agents from well-001-extract-table.mmelnyk2000.workers.dev, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-20).
Extracts structured tables from a PDF document (via URL or base64) and returns them as JSON with page numbers, headers, and rows
Extract tables from a PDF ($0.01 USDC via x402). Pass pdf_base64 or a https pdf_url. Optional schema maps headers. Optional max_pages (1-10). Returns JSON { pages, tables: [{ page, headers, rows }], warnings }. Text PDFs are parsed in-worker; scans require HOSTED_PARSER_URL.
Returns a JSON object containing: total page count processed, an array of tables (each with the page number it appeared on, an array of header strings, and a 2D array of row data), and any warnings (e.g. about scan-based pages that couldn't be parsed in-worker).
POSThttps://well-001-extract-table.mmelnyk2000.workers.dev/mcp?utm_source=zero.xyz#extract-table-from-pdf#extract-table-from-pdfChoose this endpoint when you need to programmatically extract structured tabular data from text-based PDFs and want a cheap per-call ($0.01 USDC) serverless solution. It supports both base64-encoded PDFs and HTTPS URLs, and allows optional schema mapping for known column headers. Best for text PDFs; scanned PDFs require an external hosted parser. Prefer this over general-purpose PDF tools when you need clean JSON output with per-table, per-page structure.
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