arjunprabhulal/superpdf

**Tables, charts, headings and scans to Markdown, HTML or JSON; Word, Excel and PowerPoint; forms, merging and comparing. The reader works by rules, not a language model; scans go through Tesseract OCR. Nothing is uploaded.**
**Website · Docs · Python docs · Benchmark · Changelog**
How it compares · Quick start · JavaScript/TypeScript · Python · MCP tools · How it works
npx @superpdf/cli export report.pdf --output report.md
---
superPDF reads a PDF the way it was made: from the text, fonts and drawings inside it. It rebuilds the document as
Markdown, HTML or JSON, with headings at the right level, tables with their rows and columns, and charts turned back
into the numbers they were drawn from. Scanned pages are read with OCR in 15 languages.
It runs on your computer as a command, a Python package, an MCP server for AI assistants such as Claude Code, Cursor
and Codex, or a local REST API for your own scripts. It only opens files in the folders you allow and never uploads them
(through MCP, the text your assistant reads goes to its model, as with any file you show it). It is the same reader
that powers superpdf.ai in the browser.
| Use it as | Install or run | Docs |
|---|---|---|
| Command line | npm install -g @superpdf/cli, or npx @superpdf/cli … without installing | CLI |
| Command line with Homebrew | brew install arjunprabhulal/superpdf/superpdf | Tap |
| MCP server for AI assistants | superpdf mcp --allow-dir ~/Documents/superPDF | MCP setup |
| Local REST API (OpenAPI 3.1) | superpdf serve --allow-dir ~/Documents/superPDF | API |
| JavaScript and TypeScript SDK | npm install @superpdf/cli, then import { toDocx } from '@superpdf/cli' | SDK |
| Python SDK | pip install superpdf or uv add superpdf | Python |
| Python, without installing | uvx superpdf … or pipx run superpdf … | Python |
| LangChain | pip install langchain-superpdf | Loader |
| LlamaIndex | pip install llama-index-readers-superpdf | Reader |
| LangGraph agents | the MCP server through langchain-mcp-adapters | Agents |
How it compares
On ParseBench, in **our own run** of its open-source test suite on all 2,078 documents,
superPDF scores **65.0** overall (64.8 on documents it was never tuned on). It is not on the official leaderboard yet.
The other scores are a selection from the public leaderboard (October 12, 2026).
| Parser | Overall | Tables | Charts | Content | Formatting | Grounding |
|---|---|---|---|---|---|---|
| LlamaParse Agentic Plus (paid service) | 90.2 | 93.4 | 94.2 | 92.3 | 87.1 | 84.1 |
| Claude Opus 5.5 (AI model) | 78.0 | 93.9 | 64.1 | 91.8 | 77.0 | 63.2 |
| **superPDF** (no language model, our run) | **65.0** | 68.4 | 52.2 | 80.5 | 62.3 | 61.5 |
| Azure Document Intelligence | 59.6 | 86.0 | 1.6 | 84.9 | 51.9 | 73.8 |
| Docling (docling-models) | 50.6 | 66.4 | 52.8 | 66.9 | 1.0 | 66.1 |
| Google Cloud Document AI | 50.4 | 55.1 | 1.4 | 83.7 | 50.5 | 61.3 |
| AWS Textract | 47.9 | 84.6 | 6.0 | 74.8 | 3.7 | 70.4 |
Compared with the Azure, Google and AWS services, superPDF scores much higher on charts and higher on formatting; Azure and
Textract score higher on tables. LlamaParse and Claude Opus 5.5 score higher overall. Full table and method:
superpdf.ai/performance.
Quick start
You need Node.js 22 or later.
Use it from the terminal
npx downloads the tool once and runs it. To install the superpdf command for regular use:
Or with Homebrew on macOS or Linux, which brings its own Node.js:
Use it from your AI assistant (MCP)
Create the folder the assistant may use, then add the server. For Claude Code:
For Cursor, Claude Desktop and other assistants that read an MCP settings file:
With the command installed (npm install -g @superpdf/cli), use superpdf mcp --allow-dir … in place of
npx -y @superpdf/cli mcp --allow-dir …. Then ask, for example: *"Read invoice.pdf in my superPDF folder and give me