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---
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. |