Course Link : https://euron.one/course/mcpmodel-context-protocol-masters?ref=59C2FB73
One Student One Subscription
Euron Plus - https://euron.one/personal-plan/aa2904bd-b41c-407a-b912-9dd8c75d5637?ref=940C6863
Call or WhatsApp us at: +91 9019065931
This is an AI-powered grading system using LLMs and REST APIs, built to be MCP-compatible. With minimal changes, it can be extended into a full MCP server that exposes assignment grading tools to Claude, GPT, or other agents via the Model Context Protocol.
Are you ready to Master MCP and create your very own AI-Powered Grading System?
This comprehensive video is perfect for beginners and those looking to level up their coding skills. Follow along as we guide you step by step through building a complete assignment grading system using Python, Streamlit, FastAPI, OpenAI, and Google APIs!
What You’ll Learn:
- How to set up a Python environment tailored for your project.
- The basics of Streamlit and FastAPI to create a dynamic UI and backend.
- Leveraging OpenAI and Google APIs to automate grading, plagiarism checks, and feedback generation.
- Deploying your project using Docker and cloud platforms like Render or EC2.
- Essential coding practices for a scalable and user-friendly application.
Perfect for Beginners:
Whether you're starting your programming journey or refreshing your skills, this video breaks down complex concepts into easy-to-understand steps. Get hands-on practice with real-world tools and learn how to integrate APIs into your projects.
Why Watch This Video?
- Comprehensive guidance from setup to deployment.
- Practical examples designed to help you learn programming efficiently.
- Kickstart your journey in coding with structured, beginner-friendly instruction.
#mcp #modelcontextprotocol #mcptutorial #aiagents #mcpexplained #aigradingtool #learnerfeedback #originalityreport
CHAPTERS:
00:00 - Introduction
00:52 - Project UI Design
01:50 - Project Architecture Overview
07:06 - Environment Setup Guide
10:35 - Creating a Requirements File
12:28 - Building the User Interface
18:51 - Saving Uploaded Files
20:10 - UI Navigation Path
22:04 - Tab 2 Functionality
26:00 - Tab 3 Features
27:20 - Sidebar Navigation
29:46 - OpenAI API Key Setup
32:50 - Google API Key and Custom Search Engine Setup
38:13 - Introduction to server.py
40:25 - PDF Parsing Techniques
43:15 - DOCX File Parsing
44:30 - File Processing and Plagiarism Check
52:11 - Grading System Overview
58:15 - Implementing AI Grader and Feedback
59:58 - Modifying Client.py
1:02:08 - Creating Pages in Streamlit App
1:03:47 - How to Call API Tool
1:06:54 - API Tool Usage
1:08:35 - API Tool Implementation
1:12:10 - Final Output Presentation
1:12:43 - Backend System Testing
1:13:18 - Streamlit App Testing
1:15:42 - Checking Results
1:16:00 - Conclusion and Final Words
Instagram: https://www.instagram.com/euron_official/?igsh=Z3A3cWgzdjEzaGl4&utm_source=qr
WhatsApp :https://whatsapp.com/channel/0029VaeeJwq9RZAfPW9P2l07
LinkedIn: https://www.linkedin.com/company/euronone/?viewAsMember=true
Facebook: https://www.facebook.com/people/EURON/61566117690191/