Implement storage layer and adaptive learning tools for TutorX-MCP

Refactor app.py to enhance concept graph visualization with improved error handling and response parsing. Integrate synchronous wrapper for async loading of concept graphs, update Gradio interface for better user experience, and streamline concept details display. Update concept graph tools to support LLM-driven generation with fallback mechanisms for concept retrieval.

Refactor TutorX MCP server to integrate Mistral OCR for document processing, update concept graph tools for LLM-driven responses, and enhance learning path generation with Gemini. Transitioned various tools to utilize LLM for improved educational interactions and streamlined API responses.

Refactor TutorX MCP server to remove legacy client and utility modules, update app.py for SSE integration, and enhance .gitignore to exclude .cursor directory. Clean up main.py for improved server configuration and streamline run script for better usability.