Relocate documentation files to docs/ directory and update README

fix: Update SERVER_URL to point to the production SSE endpoint

feat: Implement comprehensive UI/UX enhancements across TutorX platform

Implement AI tutoring and content generation tools for TutorX

Implement storage layer and adaptive learning tools for TutorX-MCP

Refactor: Update Gradio interface tabs and links for consistency and clarity

Refactor: Update Gradio app initialization to use create_gradio_interface function

Refactor: Update Gradio app initialization to use create_gradio_interface function

Update app.py

Fix: Start ping task when Gradio app loads to avoid event loop issues

Add periodic ping functionality to MCP server

Addind the live link for MCP SSE server.

Refactor response handling in app.py to standardize JSON output formatting. Update error management to return pretty-printed JSON for both successful and failed responses across various interaction tools, enhancing readability and consistency in data handling.

Refactor response handling in app.py and various tool modules to improve JSON parsing and error management. Introduce utility functions for cleaning and extracting JSON from text, ensuring consistent data handling across quiz, lesson, learning path, and interaction tools. Enhance robustness by accommodating multiple response formats, including strings and dictionaries, to streamline educational interactions.

Enhance quiz generation functionality by improving JSON response parsing in app.py and quiz_tools.py. Implement robust error handling for various response formats, including string and dictionary types. Introduce utility functions to clean and extract JSON from text, ensuring cleaner data handling and improved reliability in quiz data retrieval.

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.

All the functionality working with mock data

Core and Advanced Features is working with mock data.

Enhance TutorX MCP server with SSE support, update default port to 8001, and implement asynchronous API requests in Gradio interface. Added error handling for API interactions and improved server configuration.

switch mcp server stdio to sse.

Removed gamification features and deployment configuration

Added external tool integration,also with test files and documentation

Added proper MCP client, fixed Gradio-MCP integration, and improved architecture

Step 5: Added Gradio web interface and run script for the TutorX MCP server