PDF Processing

PDF Processing Guide

Overview

This skill provides enterprise-grade PDF processing using the pdf-reader MCP server (5-10x faster parallel processing) and Python fallbacks.

Quick Reference

MCP Tool Usage (Preferred)

Basic Text Extraction

{
  "sources": [{
    "path": "/path/to/document.pdf"
  }],
  "operation": "extract",
  "pages": "all"
}

Extract Specific Pages

{
  "sources": [{
    "path": "document.pdf"
  }],
  "operation": "extract",
  "pages": "1-5"
}

Get Metadata Only

{
  "sources": [{
    "path": "document.pdf"
  }],
  "operation": "metadata"
}

URL PDFs Workflow

For PDFs from URLs (like HubFS, S3, etc.):

1. Download PDF:

curl -L -o /tmp/document.pdf "https://example.com/file.pdf"

2. Extract with MCP:

{
  "sources": [{"path": "/tmp/document.pdf"}],
  "operation": "extract"
}

3. Cleanup (optional):

rm /tmp/document.pdf

Python Fallbacks

When MCP is unavailable, use Python:

Install Dependencies

pip install pypdf pdfplumber reportlab pytesseract pdf2image

Extract Text (pdfplumber)

import pdfplumber

with pdfplumber.open("document.pdf") as pdf:
    for page in pdf.pages:
        text = page.extract_text()
        print(text)

Extract Tables

import pdfplumber
import pandas as pd

with pdfplumber.open("document.pdf") as pdf:
    for page in pdf.pages:
        tables = page.extract_tables()
        for table in tables:
            df = pd.DataFrame(table[1:], columns=table[0])
            print(df)

OCR for Scanned PDFs

import pytesseract
from pdf2image import convert_from_path

images = convert_from_path('scanned.pdf')
for i, image in enumerate(images):
    text = pytesseract.image_to_string(image, lang='jpn')  # Japanese
    print(f"Page {i+1}:\n{text}")

Command-Line Tools

pdftotext (poppler-utils)

# Install on macOS
brew install poppler

# Extract text preserving layout
pdftotext -layout input.pdf output.txt

# Extract specific pages
pdftotext -f 1 -l 5 input.pdf output.txt

qpdf

# Install
brew install qpdf

# Merge PDFs
qpdf --empty --pages file1.pdf file2.pdf -- merged.pdf

# Split pages
qpdf input.pdf --pages . 1-5 -- pages1-5.pdf

Apify Integration (for complex PDFs)

For PDFs requiring advanced processing:

# PDF Text Extractor (jirimoravcik)
npx apify-cli run jirimoravcik/pdf-text-extractor \
  -i '{"pdfUrls": ["https://example.com/file.pdf"]}'

See references/apify-actors.md for full Apify integration.

Common Tasks

Anthropic Guide PDF (Example)

# Download
curl -L -o /tmp/anthropic-guide.pdf \
  "https://resources.anthropic.com/hubfs/The-Complete-Guide-to-Building-Skill-for-Claude.pdf"

# Extract with MCP
# Use pdf-reader tool with path: /tmp/anthropic-guide.pdf

Merge Multiple PDFs

from pypdf import PdfWriter, PdfReader

writer = PdfWriter()
for pdf_file in ["doc1.pdf", "doc2.pdf", "doc3.pdf"]:
    reader = PdfReader(pdf_file)
    for page in reader.pages:
        writer.add_page(page)

with open("merged.pdf", "wb") as output:
    writer.write(output)

Add Watermark

from pypdf import PdfReader, PdfWriter

watermark = PdfReader("watermark.pdf").pages[0]
reader = PdfReader("document.pdf")
writer = PdfWriter()

for page in reader.pages:
    page.merge_page(watermark)
    writer.add_page(page)

with open("watermarked.pdf", "wb") as output:
    writer.write(output)

Validation Loop

1. Extract: Run extraction
2. Verify: Check output quality
3. Retry with OCR: If text is empty/garbled, try OCR
4. Save: Store extracted content

Troubleshooting

References

• Advanced features: See references/advanced-pdf.md
• Form filling: See references/pdf-forms.md
• Apify integration: See references/apify-actors.md