Extract text

Use /extractText to read a PDF’s text by page. The output can feed search indexes, scanned-document workflows, or data extraction from invoices and reports.

Endpoint

POST /extractText

Authentication

Send a valid API key or OAuth token in the Authorization header:

Authorization: Bearer YOUR_API_KEY

See Authentication for details.

Request body

Content-Type: application/json or multipart/form-data

Note: You must provide exactly one of: pdf_base64, pdf_url, or file.

Field details

pdf_base64 (conditional)

A base64-encoded PDF file. Use this when you have the PDF data in memory or need to send it as part of a JSON payload. The encoded string should not include the data URI prefix.

pdf_url (conditional)

A publicly accessible URL where the PDF can be fetched. The server will download the PDF from this URL before processing. Supports redirects.

file (conditional, multipart only)

Upload a local PDF as multipart form data.

pages (optional)

Specify which pages to extract text from:

• JSON format: Array of integers [1, 2, 5]
• Multipart format: Comma-separated string "1,2,5"

Page numbers are 1-indexed (first page is 1, not 0). If omitted, text is extracted from all pages.

Request examples

Base64 PDF in JSON

# First, encode your PDF to base64
PDF_BASE64=$(base64 -i document.pdf)

curl -X POST https://api.pdf-mcp.io/extractText \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "pdf_base64": "'"$PDF_BASE64"'"
  }'

PDF URL

curl -X POST https://api.pdf-mcp.io/extractText \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "pdf_url": "https://example.com/documents/report.pdf"
  }'

Selected pages

curl -X POST https://api.pdf-mcp.io/extractText \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "pdf_url": "https://example.com/documents/report.pdf",
    "pages": [1, 3, 5]
  }'

Multipart file upload

curl -X POST https://api.pdf-mcp.io/extractText \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -F "file=@document.pdf"

File upload with selected pages

curl -X POST https://api.pdf-mcp.io/extractText \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -F "file=@document.pdf" \
  -F "pages=1,2,3"

Response

Success

Returns JSON with extracted text organized by page.

{
  "text": "Full combined text from all extracted pages...",
  "pages": [
    {
      "page": 1,
      "text": "Text content from page 1..."
    },
    {
      "page": 2,
      "text": "Text content from page 2..."
    }
  ],
  "total_pages": 5
}

Response fields:

Error

{
  "error": "Failed to extract text",
  "message": "Error description"
}

Status codes:

Extraction behavior

How it works

The API uses PyPDF to extract text from PDFs. This works best with:

• Native PDFs: PDFs created digitally (Word, LaTeX, HTML-to-PDF converters)
• Text-layer PDFs: Scanned documents with OCR text layer applied
• Structured PDFs: Documents with proper text encoding

Limitations

Extraction results depend on how the PDF stores its content:

• Scanned images without OCR: Pure image scans won’t have extractable text
• Complex layouts: Multi-column layouts may have text in unexpected order
• Embedded fonts: Some custom fonts may not extract properly
• Encrypted PDFs: Password-protected PDFs cannot be processed

Text order

Text is extracted in reading order as determined by the PDF structure. For complex layouts, the order may not match visual reading order. Consider post-processing if precise ordering is required.

Examples

Invoice data

curl -X POST https://api.pdf-mcp.io/extractText \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "pdf_url": "https://example.com/invoices/INV-2024-001.pdf"
  }'

Process the response to extract invoice numbers, dates, amounts, and line items.

Search indexing

curl -X POST https://api.pdf-mcp.io/extractText \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -F "file=@legal-contract.pdf"

Use the extracted text to build a searchable index of your document library.

First-page summary

curl -X POST https://api.pdf-mcp.io/extractText \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "pdf_url": "https://example.com/documents/whitepaper.pdf",
    "pages": [1]
  }'

Extract the first page when you need only its title, abstract, or summary.

Implementation notes

Choose an input method

• Upload a local file with multipart form data
• Use base64 when the PDF is already in memory
• Supply a URL for a PDF that is already hosted online

Limit processing

• Extract only the pages you need using the pages parameter
• For large PDFs, consider extracting in batches
• Cache extracted text to avoid re-processing

Process the text

• Extracted text may contain extra whitespace - normalize as needed
• Page breaks are indicated by the pages array structure
• Use the combined text field for full-document search or analysis

Handle errors

• Validate PDFs before sending (check file extension, magic bytes)
• Handle cases where pages contain no extractable text
• Implement retry logic for URL-based extraction (network failures)

Related endpoints

• Page count: get the number of pages in a PDF
• Extract pages: create a PDF from selected pages
• PDF to image: convert PDF pages to images

Credit usage

Each request costs 0.01 credits, regardless of page count.