mcp-pdf-tools/README.md
Ryan Malloy 964fd14a26 docs: cover markdown_to_pdf, [markdown] extra, uvx + pacman install
README:
- bump tool count 46 → 47, add Format Conversion bullet
- fix `claude mcp add` syntax (needs `--` separator before uvx)
- show `uvx --from "mcp-pdf[markdown]" mcp-pdf` for the new tool
- note about uvx caching + `--refresh`
- new "Format Conversion" tools subsection (markdown_to_pdf alongside pdf_to_markdown)
- new "Optional Extras" section explaining [forms], [tables], [markdown], [all]
- expand System Dependencies with Arch (pacman) and macOS (brew) recipes for
  pandoc + a PDF engine

QUICKSTART:
- replace stale `mcp-pdf-tools` package name with current `mcp-pdf`
- add uvx as the recommended end-user install path
- add pip install patterns including all optional extras
- add pacman block alongside apt-get and brew
- add markdown_to_pdf troubleshooting (mktexfmt errors, engine fallback)
- add a smoke-test snippet using the new tool
2026-05-05 16:27:28 -06:00

8.8 KiB

📄 MCP PDF

MCP PDF

A FastMCP server for PDF processing

47 tools for text extraction, OCR, tables, forms, annotations, markdown↔PDF, and more

Python 3.11+ FastMCP License: MIT PyPI

Works great with MCP Office Tools


What It Does

MCP PDF extracts content from PDFs using multiple libraries with automatic fallbacks. If one method fails, it tries another.

Core capabilities:

  • Text extraction via PyMuPDF, pdfplumber, or pypdf (auto-fallback)
  • Table extraction via Camelot, pdfplumber, or Tabula (auto-fallback)
  • OCR for scanned documents via Tesseract
  • Form handling - extract, fill, and create PDF forms
  • Document assembly - merge, split, reorder pages
  • Annotations - sticky notes, highlights, stamps
  • Vector graphics - extract to SVG for schematics and technical drawings
  • Format conversion - PDF ↔ Markdown (PDF→MD via PyMuPDF, MD→PDF via pandoc)

Quick Start

# Run from PyPI (one-shot, no permanent install)
uvx mcp-pdf

# Add to Claude Code — note the `--` separator before uvx
claude mcp add pdf-tools -- uvx mcp-pdf

# Include the markdown_to_pdf tool (requires pandoc on host)
claude mcp add pdf-tools -- uvx --from "mcp-pdf[markdown]" mcp-pdf

uvx caches tool installs aggressively. After upgrading to a new release, force a refresh with uvx --refresh mcp-pdf (or uvx --refresh --from "mcp-pdf[markdown]" mcp-pdf if you're using extras).

Development Installation
git clone https://github.com/rsp2k/mcp-pdf
cd mcp-pdf
uv sync

# System dependencies (Ubuntu/Debian)
sudo apt-get install tesseract-ocr tesseract-ocr-eng poppler-utils ghostscript

# For markdown_to_pdf:
sudo apt-get install pandoc texlive-xetex   # or: weasyprint, wkhtmltopdf

# Verify
uv run python examples/verify_installation.py

Tools

Content Extraction

Tool What it does
extract_text Pull text from PDF pages with automatic chunking for large files
extract_tables Extract tables to JSON, CSV, or Markdown
extract_images Extract embedded images
extract_links Get all hyperlinks with page filtering
ocr_pdf OCR scanned documents using Tesseract
extract_vector_graphics Export vector graphics to SVG (schematics, charts, drawings)

Format Conversion

Tool What it does
pdf_to_markdown Convert PDF to markdown preserving structure; extracts images and SVG vectors to disk
markdown_to_pdf Convert .md files (or inline text) to PDF via pandoc with auto-detected engine

markdown_to_pdf requires: pip install mcp-pdf[markdown] plus the pandoc binary and at least one PDF engine (xelatex, pdflatex, tectonic, weasyprint, or wkhtmltopdf) on PATH. The tool auto-detects what's available and uses the highest-quality one. Pass pdf_engine= to override or extra_args= for raw pandoc options.

Document Analysis

Tool What it does
extract_metadata Get title, author, creation date, page count, etc.
get_document_structure Extract table of contents and bookmarks
analyze_layout Detect columns, headers, footers
is_scanned_pdf Check if PDF needs OCR
compare_pdfs Diff two PDFs by text, structure, or metadata
analyze_pdf_health Check for corruption, optimization opportunities
analyze_pdf_security Report encryption, permissions, signatures

Forms

Tool What it does
extract_form_data Get form field names and values
fill_form_pdf Fill form fields from JSON
create_form_pdf Create new forms with text fields, checkboxes, dropdowns
add_form_fields Add fields to existing PDFs

Permit Forms (Coordinate-Based)

For scanned PDFs or forms without interactive fields. Draws text at (x, y) coordinates.

Tool What it does
fill_permit_form Fill any PDF by drawing at coordinates (works with scanned forms)
get_field_schema Get field definitions for validation or UI generation
validate_permit_form_data Check data against field schema before filling
preview_field_positions Generate PDF showing field boundaries (debugging)
insert_attachment_pages Insert image/text pages with "See page X" references

Requires: pip install mcp-pdf[forms] (adds reportlab dependency)

Document Assembly

Tool What it does
merge_pdfs Combine multiple PDFs with bookmark preservation
split_pdf_by_pages Split by page ranges
split_pdf_by_bookmarks Split at chapter/section boundaries
reorder_pdf_pages Rearrange pages in custom order

Annotations

Tool What it does
add_sticky_notes Add comment annotations
add_highlights Highlight text regions
add_stamps Add Approved/Draft/Confidential stamps
extract_all_annotations Export annotations to JSON

How Fallbacks Work

The server tries multiple libraries for each operation:

Text extraction:

  1. PyMuPDF (fastest)
  2. pdfplumber (better for complex layouts)
  3. pypdf (most compatible)

Table extraction:

  1. Camelot (best accuracy, requires Ghostscript)
  2. pdfplumber (no dependencies)
  3. Tabula (requires Java)

If a PDF fails with one library, the next is tried automatically.


Token Management

Large PDFs can overflow MCP response limits. The server handles this:

  • Automatic chunking splits large documents into page groups
  • Table row limits prevent huge tables from blowing up responses
  • Summary mode returns structure without full content
# Get first 10 pages
result = await extract_text("huge.pdf", pages="1-10")

# Limit table rows
tables = await extract_tables("data.pdf", max_rows_per_table=50)

# Structure only
tables = await extract_tables("data.pdf", summary_only=True)

URL Processing

PDFs can be fetched directly from HTTPS URLs:

result = await extract_text("https://example.com/report.pdf")

Files are cached locally for subsequent operations.


System Dependencies

Some features require system packages:

Feature Dependency
OCR tesseract-ocr
Camelot tables ghostscript
Tabula tables default-jre-headless
PDF to images poppler-utils
markdown_to_pdf pandoc + one of: texlive-xetex, texlive-latex-base, tectonic, weasyprint, wkhtmltopdf

Ubuntu/Debian:

sudo apt-get install tesseract-ocr tesseract-ocr-eng poppler-utils ghostscript default-jre-headless

# For markdown_to_pdf — pandoc plus at least one PDF engine
sudo apt-get install pandoc texlive-xetex

Arch Linux:

sudo pacman -S tesseract tesseract-data-eng poppler ghostscript jre-openjdk-headless

# For markdown_to_pdf — pandoc plus at least one PDF engine
sudo pacman -S pandoc texlive-xetex
# Lighter alternatives (pick one): tectonic, wkhtmltopdf (AUR), or pip install weasyprint

macOS (Homebrew):

brew install tesseract poppler ghostscript

# For markdown_to_pdf
brew install pandoc
brew install --cask mactex-no-gui   # for xelatex/pdflatex
# Or a lighter engine:
brew install weasyprint

Optional Extras

The base install stays lean. Heavy or niche dependencies are gated behind extras:

Extra Adds When to install
mcp-pdf[forms] reportlab Form creation tools (create_form_pdf, permit forms)
mcp-pdf[tables] camelot-py, tabula-py Higher-accuracy table extraction (also needs Java + Ghostscript)
mcp-pdf[markdown] pypandoc markdown_to_pdf tool (also needs pandoc binary)
mcp-pdf[all] All of the above Want everything

Configuration

Optional environment variables:

Variable Purpose
MCP_PDF_ALLOWED_PATHS Colon-separated directories for file output
PDF_TEMP_DIR Temp directory for processing (default: /tmp/mcp-pdf-processing)
TESSDATA_PREFIX Tesseract language data location

Development

# Run tests
uv run pytest

# With coverage
uv run pytest --cov=mcp_pdf

# Format
uv run black src/ tests/

# Lint
uv run ruff check src/ tests/

License

MIT