Lepuroshi - AI-Powered Scheduling Service Platform

Overview

Lepuroshi is an innovative scheduling service platform that combines modern web technologies with artificial intelligence to revolutionize appointment management. Built with React frontend and .NET backend, the platform features a unique Model Context Protocol (MCP) server that enables AI agents to understand, process, and manage scheduling requests through natural language interactions.

Key Features

AI-Powered Scheduling

Natural Language Processing: AI agents can interpret scheduling requests in conversational language
Intelligent Conflict Resolution: Automatic detection and resolution of scheduling conflicts
Smart Suggestions: AI-driven recommendations for optimal appointment times
Context-Aware Booking: Understanding of user preferences and historical patterns

MCP Server Integration

Model Context Protocol: Custom MCP server implementation for AI agent communication
Real-time Communication: Seamless data exchange between AI agents and scheduling system
Standardized Interface: Protocol-compliant communication for reliable AI interactions
Extensible Architecture: Modular design allowing for future AI model integrations

Appointment Management

Multi-Calendar Support: Integration with various calendar systems and providers
Automated Notifications: Email and SMS reminders for upcoming appointments
Recurring Appointments: Support for repeating schedules and series bookings
Availability Management: Dynamic availability tracking and slot management

User Experience

Intuitive Interface: Clean, responsive React-based user interface
Real-time Updates: Live synchronization of schedule changes across all devices
Mobile Optimization: Progressive web app capabilities for mobile scheduling
Multi-language Support: Internationalization for global user base

Technical Architecture

Frontend Development

React 18: Modern React with hooks and concurrent features for optimal performance
TypeScript: Type-safe development ensuring code reliability and maintainability
State Management: Advanced state management for complex scheduling workflows
Component Library: Reusable UI components for consistent user experience

Backend Infrastructure

ASP.NET Core: High-performance .NET backend with RESTful API architecture
Entity Framework: Object-relational mapping for efficient database operations
SignalR: Real-time communication for live schedule updates
Authentication: Secure user authentication and authorization systems

MCP Server Implementation

Custom Protocol Handler: Specialized MCP server for AI agent communication
JSON-RPC Interface: Standardized communication protocol for AI interactions
Resource Management: Efficient handling of scheduling resources and constraints
Tool Integration: Custom tools for appointment creation, modification, and cancellation

Database & Storage

SQL Server: Robust relational database for appointment and user data
Redis Cache: High-performance caching for frequently accessed scheduling data
Blob Storage: Secure storage for user files and appointment attachments
Data Encryption: End-to-end encryption for sensitive scheduling information

AI Integration Features

Conversational Scheduling

Natural Language Understanding: Parse complex scheduling requests from users
Intent Recognition: Identify scheduling actions from conversational input
Entity Extraction: Extract dates, times, participants, and locations from text
Contextual Responses: Generate human-like responses for scheduling confirmations

Intelligent Automation

Smart Rescheduling: Automatic rescheduling based on conflicts and preferences
Predictive Analytics: Forecast scheduling patterns and optimize availability
Workflow Automation: Automated follow-ups and appointment lifecycle management
Integration Capabilities: Connect with external systems through AI-mediated APIs

Performance & Scalability

System Optimization

Microservices Architecture: Scalable service-oriented design for high availability
Load Balancing: Distributed processing for handling concurrent scheduling requests
Caching Strategies: Multi-layer caching for optimal response times
Database Optimization: Indexed queries and optimized data structures

Security & Compliance

Data Protection: GDPR-compliant data handling and user privacy protection
API Security: OAuth 2.0 and JWT token-based authentication
Audit Logging: Comprehensive logging for security and compliance monitoring
Encryption: TLS encryption for all data transmission

Business Impact

Lepuroshi transforms traditional scheduling workflows by:

Reducing Manual Work: AI automation eliminates repetitive scheduling tasks
Improving Accuracy: Intelligent conflict detection prevents double-bookings
Enhancing User Experience: Natural language interactions make scheduling intuitive
Increasing Efficiency: Automated workflows reduce administrative overhead
Enabling Scalability: AI-powered system handles growing scheduling demands

Technical Stack

Frontend

React 18 with TypeScript for type-safe component development
Material-UI or Tailwind CSS for modern, responsive design
React Query for efficient data fetching and caching
React Router for client-side navigation

Backend

.NET 8 with ASP.NET Core for high-performance web APIs
Entity Framework Core for database operations
SignalR for real-time communication
AutoMapper for object-to-object mapping

AI & Integration

Custom MCP Server for AI agent communication
OpenAI API integration for natural language processing
Webhook Support for external system integrations
RESTful APIs for third-party calendar integrations

Infrastructure

Azure/AWS cloud hosting for scalability and reliability
Docker containerization for consistent deployments
CI/CD Pipelines for automated testing and deployment
Monitoring & Analytics for system performance tracking

This project showcases the cutting-edge integration of AI technology with traditional scheduling systems, demonstrating expertise in full-stack development, AI integration, and modern software architecture patterns.