---
title: IPMentor
emoji: 🌐
colorFrom: blue
colorTo: green
sdk: gradio
sdk_version: 5.33.1
app_file: app.py
pinned: false
license: mit
short_description: IPv4 networking toolkit with verified calculations
tags:
  - Agents-MCP-Hackathon
  - mcp-server-track
  - networking
  - education
  - ipv4
  - subnet-calculator
  - ai-tutoring
---

# IPMentor 🌐

**IPMentor** is an IPv4 networking toolkit designed as verified computational tools for AI tutoring systems. Built for the **Gradio MCP Hackathon 2025**, this project demonstrates how MCP can bridge AI tutoring systems with specialized computational tools, creating more reliable and cost-effective educational experiences.

## 🎯 Hackathon Track: MCP Server/Tool

This Gradio app serves as both an interactive web interface and an **MCP Server**, providing three core networking tools that AI agents can access through the Model Context Protocol:

- `ip_info` - Analyze IPv4 addresses and subnet masks
- `subnet_calculator` - Perform subnet calculations with multiple division methods  
- `generate_diagram` - Create visual network diagrams

## 🏆 Competing for Mistral AI Choice Award

This project uses **Mistral Small 3.1 24B Instruct** in the AI chatbot demo, showcasing how smaller, efficient models can handle educational interactions while delegating precise calculations to IPMentor's verified tools.

## 🎥 Demo Video

Video demonstration: [assets/ipmentor-demo.mp4](assets/ipmentor-demo.mp4)

## 🤖 Live AI Chatbot Demo

Experience IPMentor in action with an Mistral Small 3.1 24B Instruct: [ipmentor-demo](https://huggingface.co/spaces/Agents-MCP-Hackathon/ipmentor-demo)

## 💡 Why IPMentor?

Current AI tutoring faces a challenge: while LLMs can perform calculations, they occasionally make errors and using powerful models for every calculation is expensive. IPMentor solves this by:

- **Verified Calculations**: All subnet mathematics uses dedicated algorithms, eliminating computational errors
- **Cost-Effective AI**: Smaller models handle pedagogy while IPMentor handles precise calculations
- **Educational Focus**: Designed specifically for networking education scenarios

## 🔗 Links

- **GitHub Repository**: [https://github.com/DavidLMS/ipmentor](https://github.com/DavidLMS/ipmentor)
- **AI Chatbot Demo**: [https://huggingface.co/spaces/Agents-MCP-Hackathon/ipmentor-demo](https://huggingface.co/spaces/Agents-MCP-Hackathon/ipmentor-demo)

## 🛠️ Technical Architecture

Built with Python, Gradio, native IPv4 algorithms, D2 for diagrams, MCP protocol support, and Pydantic validation. This creates a reliable foundation for AI-powered networking education.

**Integration Focus**: IPMentor is designed to complement [LearnMCP-xAPI](https://github.com/DavidLMS/learnmcp-xapi) for comprehensive AI tutoring systems. While IPMentor provides verified computational tools, LearnMCP-xAPI maintains persistent learning records, enabling AI tutors that can both perform accurate calculations and adapt to individual student learning patterns over time.