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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)
## 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
---
## 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
- **Local Access:** Browser-based access from local machine
---
## 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:** Analytics and performance monitoring
---
## 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
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