pdf_oxide is a free, open source data extraction & web scraping project written in Rust and released under Apache-2.0. It has 1,156 GitHub stars, 147 forks and 322 open issues, and was last pushed 3 days ago. On this registry it ranks #111 of 149 tracked projects in Data Extraction & Web Scraping, with 5 head-to-head comparisons available. It gained 100 stars over the last 30 tracked days.

What is pdf_oxide?

PDFOxide is a Rust-core PDF toolkit with bindings for nineteen additional languages, plus a command-line tool and an MCP server, aimed at developers and data teams that need fast, permissively licensed text extraction, image extraction, markdown conversion, and PDF creation and editing.

What it is

PDFOxide is a PDF library built on a Rust core and shipped as idiomatic bindings for nineteen further languages, including Python, Go, JavaScript and TypeScript, C#/.NET, Java, Kotlin, Scala, Clojure, Ruby, PHP, C++, Objective-C, Swift, Dart, R, Julia, Zig, Elixir, and WASM, for a total of twenty supported languages. It also ships a pdf-oxide CLI and a pdf-oxide-mcp server that exposes document handling to AI assistants. The project is dual licensed under MIT and Apache-2.0, hosts its documentation at oxide.fyi, and publishes to crates.io, PyPI, npm, and a Homebrew tap.

The concrete problem it solves is slow and licence-encumbered document parsing. PDFOxide reports a 0.8ms mean per document, which it measures as five times faster than PyMuPDF, fifteen times faster than pypdf, and twenty-nine times faster than pdfplumber, with a 100% pass rate on 3,830 real-world PDFs drawn from veraPDF, Mozilla pdf.js, and DARPA SafeDocs. It replaces both the incumbent Python parsing libraries and, for teams that cannot accept AGPL-3.0 or GPL-3.0 terms, the licence itself: PyMuPDF and pymupdf4llm are AGPL-3.0 and pdftext is GPL-3.0, while PDFOxide is MIT/Apache-2.0.

Key capabilities

  • Text extraction through the lazy page.text property in Python and extract_text(0) in Rust, with per-character data available via the lazy page.chars property.
  • Image extraction through extract_images(0) on a document handle.
  • Markdown conversion with structure detection, via page.markdown(detect_headings=True), doc.to_markdown(0, Default::default()), or the CLI command pdf-oxide markdown document.pdf -o output.md.
  • PDF creation and editing, including merging with pdf-oxide merge a.pdf b.pdf -o combined.pdf.
  • Content search from the shell with pdf-oxide search document.pdf "pattern", and windowed text output with pdf-oxide text document.pdf.
  • An MCP server, pdf-oxide-mcp, configured as an mcpServers entry for Claude Desktop, Claude Code, or Cursor.
  • A WASM build published to npm as pdf-oxide-wasm, alongside the native bindings.

Who uses it and how

  • Data and analytics teams building extraction pipelines over large PDF corpora, where the reported 0.8ms mean and 9ms p99 translate directly into throughput.
  • Retrieval and LLM preprocessing work, served by the pdf-to-markdown and llm topics and the heading-aware markdown conversion path.
  • Polyglot engineering organisations that need one parsing semantics across services written in Python, Go, Java, C#, or TypeScript rather than a different library per runtime.
  • AI assistant integrations that mount the MCP server to give a coding agent direct read access to local PDFs.
  • Shell and batch workflows that call the pdf-oxide CLI instead of embedding a library, including Homebrew installs on developer machines.

Getting started

Install per language: pip install pdf_oxide for Python, pdf_oxide = "0.3" under [dependencies] for Rust, brew install yfedoseev/tap/pdf-oxide for the CLI and MCP server, or pdf-oxide-wasm from npm for the browser build. The Python entry point is from pdf_oxide import PdfDocument used as a context manager.

How it compares

Within its own benchmark table, PDFOxide sits against PyMuPDF, pypdfium2, pymupdf4llm, pdftext, and pdfminer, and the facts position it as the fastest of that set with the only 100% pass rate shown. Its licence is also the most permissive in that group: pypdfium2 is Apache-2.0 and pdfminer is MIT, but PyMuPDF, pymupdf4llm, and pdftext carry AGPL-3.0 or GPL-3.0 obligations. No list of paid products it replaces is provided, so the comparison stops there.

When to use it — and when not to

Nothing needs to be operated: PDFOxide is a library, a CLI, and an MCP server, with no database, object storage, or SMTP dependency mentioned, so the operational cost of adoption is packaging rather than infrastructure. It should not be chosen by teams that need OCR, since the benchmark explicitly covers text-extraction libraries only and excludes OCR. The version is still 0.3.x with 322 open issues, so teams that require a frozen, long-stable API surface or a large third-party answer corpus should weigh that before committing; the breadth of twenty language bindings also implies a wide surface that a single maintainer must keep in step.

project readme (upstream, from github) — read inline

PDFOxide - The Fastest PDF Toolkit for 20 Languages — Python, Rust, Go, JS/TS, C#, Java, Kotlin, Swift, C++ & more, plus CLI & AI

New in v0.3.69 — eleven new language bindings. PDFOxide now ships idiomatic bindings for C++, Swift, Kotlin, Dart, R, Julia, Zig, Scala, Clojure, Objective-C, and Elixir, each built over the stable C ABI with its own CI workflow, api-coverage tests, and runnable examples. That brings the toolkit to 20 languages (Rust core + 19 bindings). Want another language? Open an issue and tell us.

The fastest PDF library for text extraction, image extraction, and markdown conversion. A Rust core with bindings for 19 languages — Python, Go, JavaScript / TypeScript, C# / .NET, Java, Kotlin, Scala, Clojure, Ruby, PHP, C++, Objective-C, Swift, Dart, R, Julia, Zig, Elixir, and WASM — plus a CLI tool and MCP server for AI assistants. 0.8ms mean per document, 5× faster than PyMuPDF, 15× faster than pypdf. 100% pass rate on 3,830 real-world PDFs. MIT licensed.

Crates.io PyPI PyPI Downloads npm Documentation Build Status License: MIT OR Apache-2.0

Quick Start

Python

from pdf_oxide import PdfDocument

with PdfDocument("paper.pdf") as doc:
    print(len(doc))                          # number of pages
    for page in doc:
        text = page.text                     # lazy property
        chars = page.chars                   # lazy property
        md = page.markdown(detect_headings=True)

# Direct page access by index
doc = PdfDocument("paper.pdf")
page = doc[0]
text = page.text
pip install pdf_oxide

Rust

use pdf_oxide::PdfDocument;

let mut doc = PdfDocument::open("paper.pdf")?;
let text = doc.extract_text(0)?;
let images = doc.extract_images(0)?;
let markdown = doc.to_markdown(0, Default::default())?;
[dependencies]
pdf_oxide = "0.3"

CLI

pdf-oxide text document.pdf
pdf-oxide markdown document.pdf -o output.md
pdf-oxide search document.pdf "pattern"
pdf-oxide merge a.pdf b.pdf -o combined.pdf
brew install yfedoseev/tap/pdf-oxide

MCP Server (for AI assistants)

# Install
brew install yfedoseev/tap/pdf-oxide   # includes pdf-oxide-mcp

# Configure in Claude Desktop / Claude Code / Cursor
{
  "mcpServers": {
    "pdf-oxide": { "command": "crgx", "args": ["pdf_oxide_mcp@latest"] }
  }
}

Why PDFOxide?

  • Fast — 0.8ms mean per document, 5× faster than PyMuPDF, 15× faster than pypdf, 29× faster than pdfplumber
  • Reliable — 100% pass rate on 3,830 test PDFs, zero panics, zero timeouts
  • Complete — Text extraction, image extraction, PDF creation, and editing in one library
  • Multi-platform — 20 languages (Rust core + 19 bindings: Python, Go, JS/TS, C#/.NET, Java, Kotlin, Scala, Clojure, Ruby, PHP, C++, Objective-C, Swift, Dart, R, Julia, Zig, Elixir, WASM), plus a CLI and MCP server for AI assistants
  • Permissive license — MIT / Apache-2.0 — use freely in commercial and open-source projects

Performance

Benchmarked on 3,830 PDFs from three independent public test suites (veraPDF, Mozilla pdf.js, DARPA SafeDocs). Text extraction libraries only (no OCR). Single-thread, 60s timeout, no warm-up.

Python Libraries

Library Mean p99 Pass Rate License
PDFOxide 0.8ms 9ms 100% MIT
PyMuPDF 4.6ms 28ms 99.3% AGPL-3.0
pypdfium2 4.1ms 42ms 99.2% Apache-2.0
pymupdf4llm 55.5ms 280ms 99.1% AGPL-3.0
pdftext 7.3ms 82ms 99.0% GPL-3.0
pdfminer 16.8ms 124ms 98.8% MIT
pdfplumber 23.2ms 189ms 98.8% MIT
markitdown 108.8ms 378ms 98.6% MIT
pypdf 12.1ms 97ms 98.4% BSD-3

Rust Libraries

Library Mean p99 Pass Rate Text Extraction
PDFOxide 0.8ms 9ms 100% Built-in
oxidize_pdf 13.5ms 11ms 99.1% Basic
unpdf 2.8ms 10ms 95.1% Basic
pdf_extract 4.08ms 37ms 91.5% Basic
lopdf 0.3ms 2ms 80.2% No built-in extraction

Text Quality

99.5% text parity vs PyMuPDF and pypdfium2 across the full corpus. PDFOxide extracts text from 7–10× more "hard" files than it misses vs any competitor.

Corpus

Suite PDFs Pass Rate
veraPDF (PDF/A compliance) 2,907 100%
Mozilla pdf.js 897 99.2%
SafeDocs (targeted edge cases) 26 100%
Total 3,830 100%

100% pass rate on all valid PDFs — the 7 non-passing files across the corpus are intentionally broken test fixtures (missing PDF header, fuzz-corrupted catalogs, invalid xref streams).

Features

Extract Create Edit
Text & Layout Documents Annotations
Images Tables Form Fields
Forms Graphics Bookmarks
Annotations Templates Links
Bookmarks Images Content

Python API

Page-oriented API

from pdf_oxide import PdfDocument

with PdfDocument("report.pdf") as doc:
    print(len(doc))          # page count
    print(doc.version())

    # Iterate or index pages
    for page in doc:
        text   = page.text                      # str, lazy
        chars  = page.chars                     # list[TextChar], lazy
        words  = page.words                     # list[Word], lazy
        lines  = page.lines                     # list[TextLine], lazy
        tables = page.tables                    # list[Table], lazy
        images = page.images                    # list[Image], lazy
        md     = page.markdown(detect_headings=True)
        html   = page.html()
        print(f"Page {page.index}: {page.width:.0f}×{page.height:.0f} pts")

    # Direct index access (supports negative indices)
    first = doc[0]
    last  = doc[-1]

Scoped extraction

# Extract from a region: (x, y, width, height) in PDF points
header = doc.within(0, (0, 700, 612, 92)).extract_text()
region = doc.within(0, (50, 400, 500, 200))
region_words  = region.extract_words()
region_images = region.extract_images()

Extraction profiles

from pdf_oxide import ExtractionProfile

# Pre-tuned profiles for different document types
words = doc.extract_words(0, profile=ExtractionProfile.form())
lines = doc.extract_text_lines(0, profile=ExtractionProfile.academic())

# Override adaptive thresholds (in PDF points)
words = doc.extract_words(0, word_gap_threshold=2.5)
lines = doc.extract_text_lines(0, word_gap_threshold=2.5, line_gap_threshold=4.0)
params = doc.page_layout_params(0)
print(f"word gap: {params.word_gap_threshold:.1f}")

Form Fields

# Extract form fields
fields = doc.get_form_fields()
for f in fields:
    print(f"{f.name} ({f.field_type}) = {f.value}")

# Fill and save
doc.set_form_field_value("employee_name", "Jane Doe")
doc.set_form_field_value("wages", "85000.00")
doc.save("filled.pdf")

Rust API

use pdf_oxide::PdfDocument;

fn main() -> Result<(), Box<dyn std::error::Error>> {
    let mut doc = PdfDocument::open("paper.pdf")?;

    // Extract text
    let text = doc.extract_text(0)?;

    // Character-level extraction
    let chars = doc.extract_chars(0)?;

    // Extract images
    let images = doc.extract_images(0)?;

    // Vector graphics
    let paths = doc.extract_paths(0)?;

    Ok(())
}

Form Fields (Rust)

use pdf_oxide::editor::{DocumentEditor, EditableDocument, SaveOptions};
use pdf_oxide::editor::form_fields::FormFieldValue;

let mut editor = DocumentEditor::open("w2.pdf")?;
editor.set_form_field_value("employee_name", FormFieldValue::Text("Jane Doe".into()))?;
editor.save_with_options("filled.pdf", SaveOptions::incremental())?;

Installation

Python

pip install pdf_oxide

Wheels available for Linux, macOS, and Windows. Python 3.8–3.14.

Rust

[dependencies]
pdf_oxide = "0.3"

JavaScript/WASM

npm install pdf-oxide-wasm
const { WasmPdfDocument } = require("pdf-oxide-wasm");

CLI

brew install yfedoseev/tap/pdf-oxide    # Homebrew (macOS/Linux)
cargo install pdf_oxide_cli             # Cargo
cargo binstall pdf_oxide_cli            # Pre-built binary via cargo-binstall

MCP Server

brew install yfedoseev/tap/pdf-oxide    # Included with CLI in Homebrew
cargo install pdf_oxide_mcp             # Cargo

Other languages

Established bindings:

  • Go — go get github.com/yfedoseev/pdf_oxide/go — see go/README.md
  • JavaScript / TypeScript (Node.js) — npm install pdf-oxide — see js/README.md
  • C# / .NET — dotnet add package PdfOxide — see csharp/README.md
  • Java (JDK 11+) — Maven coords fyi.oxide:pdf-oxide:0.3.70 — see java/README.md
  • Ruby — gem install pdf_oxide — see ruby/README.md
  • PHP — composer require oxide/pdf-oxide — see php/README.md

New in v0.3.69 (all over the stable C ABI):

<!-- Java (Maven) -->
<dependency>
  <groupId>fyi.oxide</groupId>
  <artifactId>pdf-oxide</artifactId>
  <version>0.3.70</version>
</dependency>
// Kotlin (Gradle, Kotlin DSL)
implementation("fyi.oxide:pdf-oxide-kotlin:0.3.70")

Every binding shares the same Rust core, so a bug fix in one lands in all of them — everything you read in this README applies, just with each language's native naming conventions. Publishing details for each registry are in docs/RELEASING-bindings.md.

CLI

22 commands for PDF processing directly from your terminal:

pdf-oxide text report.pdf                      # Extract text
pdf-oxide markdown report.pdf -o report.md     # Convert to Markdown
pdf-oxide html report.pdf -o report.html       # Convert to HTML
pdf-oxide info report.pdf                      # Show metadata
pdf-oxide search report.pdf "neural.?network"  # Search (regex)
pdf-oxide images report.pdf -o ./images/       # Extract images
pdf-oxide merge a.pdf b.pdf -o combined.pdf    # Merge PDFs
pdf-oxide split report.pdf -o ./pages/         # Split into pages
pdf-oxide watermark doc.pdf "DRAFT"            # Add watermark
pdf-oxide forms w2.pdf --fill "name=Jane"      # Fill form fields

Run pdf-oxide with no arguments for interactive REPL mode. Use --pages 1-5 to process specific pages, --json for machine-readable output.

MCP Server

pdf-oxide-mcp lets AI assistants (Claude, Cursor, etc.) extract content from PDFs locally via the Model Context Protocol.

Add to your MCP client configuration:

{
  "mcpServers": {
    "pdf-oxide": { "command": "crgx", "args": ["pdf_oxide_mcp@latest"] }
  }
}

The server exposes an extract tool that supports text, markdown, and HTML output formats with optional page ranges and image extraction. All processing runs locally — no files leave your machine.

Building from Source

# Clone and build
git clone https://github.com/yfedoseev/pdf_oxide
cd pdf_oxide
cargo build --release

# Run tests
cargo test

# Build Python bindings
maturin develop

# Build the shared library for Go, JS/TS, and C# bindings
cargo build --release --lib
# Output: target/release/libpdf_oxide.{so,dylib} or pdf_oxide.dll

Documentation

Use Cases

  • RAG / LLM pipelines — Convert PDFs to clean Markdown for retrieval-augmented generation with LangChain, LlamaIndex, or any framework
  • AI assistants — Give Claude, Cursor, or any MCP-compatible tool direct PDF access via the MCP server
  • Document processing at scale — Extract text, images, and metadata from thousands of PDFs in seconds
  • Data extraction — Pull structured data from forms, tables, and layouts
  • Academic research — Parse papers, extract citations, and process large corpora
  • PDF generation — Create invoices, reports, certificates, and templated documents programmatically
  • PyMuPDF alternative — MIT licensed, 5× faster, no AGPL restrictions

Notable Users

PDFOxide is a production dependency of RAG engines, collaborative editors, AI coding agents, and arXiv.org's own submission pipeline. Every entry below is verified against that project's public dependency manifest — no self-reported logos, no "trusted by" wall.

Star counts checked 2026-08-21:

  • RAGFlow (89k★) — one of the most popular open-source RAG engines; PDFOxide is the primary PDF engine in its deepdoc parsing pipeline (go.mod)
  • AFFiNE (71.7k★) — open-source Notion/Miro alternative; powers document extraction via AFFiNE's own doc_extractor crate (Cargo.toml)
  • grok-build (25.8k★) — xAI's coding-agent TUI; uses PDFOxide's rendering feature to read PDFs in a repo (Cargo.toml)
  • create-context-graph (Neo4j Labs, 712★) — GraphRAG context-builder; PDFOxide is its primary PDF parser (pyproject.toml)
  • arXiv submission-tools — arXiv.org's own PDF validation and LaTeX-to-PDF submission pipeline

Using PDFOxide in production? Open an issue to be added here.

Why I built this

I needed PyMuPDF's speed without its AGPL license, and I needed it in more than one language. Nothing existed that ticked all three boxes — fast, MIT, multi-language — so I wrote it. The Rust core is what does the real work; the bindings for Python, Go, JS/TS, C#, and WASM are thin shells around the same code, so a bug fix in one lands in all of them. It now passes 100% of the veraPDF + Mozilla pdf.js + DARPA SafeDocs test corpora (3,830 PDFs) on every platform I've tested.

If it's useful to you, a star on GitHub genuinely helps. If something's broken or missing, open an issue — I read all of them.

— Yury

License & trademark

The code is dual-licensed under MIT or Apache-2.0 at your option. Unlike AGPL-licensed alternatives, pdf_oxide can be used freely in any project — commercial or open-source — with no copyleft restrictions.

The name and brand are not covered by the code license: "PDFOxide" (the product name) and "pdf_oxide" (the package name), together with any associated logo, are trademarks of Yury Fedoseev. You may say your product "uses PDFOxide"; please don't name a different or modified product "PDFOxide" or "pdf_oxide". See TRADEMARKS.md, and FORKS.md if you are forking.

© 2025–2026 Yury Fedoseev and the PDFOxide contributors. Contributions are accepted under the project's DCO and CLA; contributors retain ownership of their work.

Contributing

We welcome contributions! See CONTRIBUTING.md for guidelines.

cargo build && cargo test && cargo fmt && cargo clippy -- -D warnings

Citation

@software{pdf_oxide,
  title = {PDFOxide: Fast Multi-Language PDF Toolkit (Rust core, 19 language bindings)},
  author = {Yury Fedoseev},
  year = {2025},
  url = {https://github.com/yfedoseev/pdf_oxide}
}

20 languages (Rust + Python + Go + JS/TS + C# + Java + Kotlin + Scala + Clojure + Ruby + PHP + C++ + Objective-C + Swift + Dart + R + Julia + Zig + Elixir + WASM) + CLI + MCP | MIT/Apache-2.0 | 100% pass rate on 3,830 PDFs | 0.8ms mean | 5× faster than the industry leaders

Frequently asked questions

Is pdf_oxide free to use?

pdf_oxide is open source under the Apache-2.0 licence. There is no licence fee and no seat count — you can self-host it or, where the project offers one, pay a vendor for a managed version instead.

What does pdf_oxide do?

The fastest PDF library for Python and Rust. Text extraction, image extraction, markdown conversion, PDF creation & editing. 0.8ms mean, 5× faster than industry

What is pdf_oxide written in?

pdf_oxide is primarily written in Rust. Its source is publicly available at https://github.com/yfedoseev/pdf_oxide, and it has 1,156 GitHub stars.