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Step 1: Initial TutorX MCP server setup with basic core features
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TutorX-MCP

Product Requirements Document (PRD)

Educational AI Tutor MCP Server

1. Overview

Product Name:

Educational AI Tutor MCP Server

Purpose:

To provide an adaptive, multi-modal, and collaborative AI tutoring platform accessible via browser, leveraging Model Context Protocol (MCP) for tool integration and Gradio for user-friendly interfaces.

Target Users:

  • Students: K-12, higher education, lifelong learners
  • Teachers: For classroom integration and progress monitoring
  • Administrators: For curriculum management and analytics

2. Objectives

  • Deliver personalized, adaptive learning experiences
  • Enable collaborative and interactive learning
  • Support multiple input/output modalities (text, voice, handwriting, AR/VR)
  • Ensure privacy and data security
  • Integrate with external educational tools and standards
  • Provide actionable insights and analytics for students and teachers

3. Features

3.1 Core Features

  • Adaptive Learning Engine
    • Concept graph with 50,000+ nodes (STEM and humanities)
    • Dynamic skill assessment and competency tracking
    • Personalized learning paths based on real-time feedback
  • Multi-Modal Interaction
    • Text-based Q&A with error pattern recognition
    • Voice recognition with ASR and TTS
    • Handwriting recognition and digital ink processing
  • Assessment Suite
    • Automated quiz and problem generation
    • Step-by-step solution analysis
    • Plagiarism and similarity detection
  • Feedback System
    • Contextual error analysis and suggestions
    • Multimodal feedback (text, audio, visual)
    • Emotional state recognition (via webcam/EEG)

3.2 Advanced Features

  • Neurological Engagement Monitor
    • Integration with consumer-grade EEG devices
    • Attention, cognitive load, and stress detection
  • Cross-Institutional Knowledge Fusion
    • Curriculum alignment with 10+ national standards
    • Textbook content reconciliation
    • Cultural adaptation engine
  • Automated Lesson Authoring
    • AI-powered content generation from PDFs, videos, web

3.3 User Experience

  • Custom Dashboard
    • Knowledge growth map
    • Temporal performance heatmap
    • Cognitive profile radar
  • Accessibility
    • Screen reader compatibility
    • Text-to-speech and adjustable interface
  • Gamification
    • Badges, leaderboards, token-based rewards

4. Technical Requirements

  • MCP Server: Exposes all core and advanced features as MCP tools
  • Gradio Interface: User-friendly, customizable, and accessible
  • Microservices Architecture: Modular design for scalability
  • Real-Time Data Processing: Asynchronous task queues and caching
  • Cloud Deployment: Browser-based access with no local setup
  • Integration: Supports external APIs, LMS, and educational tools

5. Non-Functional Requirements

  • Performance: Supports 100+ concurrent users with <1s response time for core features
  • Security: End-to-end encryption, role-based access control
  • Privacy: Compliant with GDPR, COPPA, and FERPA
  • Scalability: Horizontally scalable to support large institutions
  • Accessibility: WCAG 2.1 AA compliant

6. Success Metrics

  • User Engagement: Average session duration, repeat usage
  • Learning Outcomes: Improvement in quiz/test scores
  • Adoption Rate: Number of active users and institutions
  • Teacher Satisfaction: Feedback on usability and effectiveness
  • Technical Performance: Uptime, response time, error rates

7. Roadmap

  1. Phase 1: Core adaptive learning engine and MCP integration
  2. Phase 2: Multi-modal interaction and collaborative tools
  3. Phase 3: Advanced features (engagement monitor, lesson authoring)
  4. Phase 4: Deployment, analytics, and gamification

8. Risks and Mitigation

  • Privacy Concerns: Implement strict data controls and transparency
  • Technical Complexity: Modular design and clear documentation
  • User Adoption: Provide training materials and support

9. Stakeholders

  • Product Manager: Oversees development and alignment with educational goals
  • Developers: Build and maintain the MCP server and Gradio interface
  • Designers: Ensure intuitive and accessible user experience
  • Educators: Provide feedback and guide curriculum alignment
  • Students: End users and primary beneficiaries

10. Appendix

  • Glossary: MCP, Gradio, adaptive learning, etc.
  • References: Educational standards, privacy regulations, technical documentation