README.md
AI-Powered Customer Service Automation for Weather-Related Flight Disruptions
Airline Flight Delays MCP Server
AI-Powered Customer Service Automation for Weather-Related Flight Disruptions
📋 Overview
This project presents a Model Context Protocol (MCP) server-based system designed to reduce customer support costs for Indigo airline during weather-related flight delays. The airline operates a major hub in Mumbai with over 5,000 daily flights and faces peak support demand, long wait times, customer dissatisfaction, and high operational costs during delays.
Key Innovations
- Mood-Aware Communication: Adapts tone based on passenger sentiment (frustrated, concerned, calm, excited)
- Proactive Engagement: Entertainment activities scaled to delay duration (30min to 3+ hours)
- Personalized Service: Prioritizes frequent flyer members and provides customized recommendations
- Seamless Human Handoff: Full conversation context preservation for specialist escalation
- Real-Time Intelligence: Live flight status, rebooking options, and destination insights
Expected Results
- 60-70% reduction in routine customer service inquiries through automation
- Instant response times for common queries
- Intelligent routing of complex cases to human specialists
- Enhanced customer satisfaction through personalized, empathetic service
🏗️ Architecture
The solution uses a microservices architecture with six specialized MCP servers coordinated by a main orchestrator:
┌─────────────────────────────────────────────────────────────┐
│ Main MCP Orchestrator │
│ (FastMCP Server - Python) │
└─────────────────────────────────────────────────────────────┘
│
┌─────────────────────┼─────────────────────┐
│ │ │
▼ ▼ ▼
┌──────────────┐ ┌──────────────┐ ┌──────────────┐
│Authentication│ │ Flight │ │ Mood │
│ Server │ │ Information │ │ Analysis │
│ │ │ Server │ │ Server │
└──────────────┘ └──────────────┘ └──────────────┘
│ │ │
▼ ▼ ▼
┌──────────────┐ ┌──────────────┐ ┌──────────────┐
│ Engagement/ │ │ Itinerary/ │ │ Human │
│ Games │ │ Food │ │ Agent │
│ Server │ │ Server │ │ Transfer │
└──────────────┘ └──────────────┘ └──────────────┘
1. **Authentication Server**
- Secure passenger login and session management
- PNR/email/frequent flyer number authentication
- JWT token generation
- Passenger profile retrieval
2. **Flight Information Server**
- Real-time flight status and delay information
- Gate details and terminal navigation
- Alternative flight options for rebooking
- Connection impact analysis
- Weather delay notifications
3. **Mood Analysis Server**
- Sentiment detection using VADER and TextBlob
- LLM-powered emotional intelligence analysis
- Communication tone recommendations
- Escalation trigger detection
- Sentiment trend tracking
4. **Engagement/Games Server**
- Delay-appropriate entertainment activities
- Interactive games, trivia, and quizzes
- Destination virtual tours
- Relaxation and mindfulness exercises
- Airport exploration suggestions
5. **Itinerary/Food Server**
- Airport restaurant recommendations
- Destination dining guides
- Attraction and activity planning
- Personalized itinerary generation
- Dietary restriction handling
6. **Human Agent Transfer Server**
- Context-aware escalation to specialists
- Complete conversation history preservation
- Priority queue management
- Passenger profile and sentiment handoff
- Intelligent routing based on issue complexity
🚀 Quick Start
Prerequisites
- Python: 3.9 or higher
- PostgreSQL: 12+ with pgvector extension
- Redis: 6+ (optional, for caching)
- LLM API: OpenAI, Azure OpenAI, or Anthropic API key
Installation
- Clone the Repository
cd /path/to/your/workspace
git clone <repository-url>
cd airline-delays-mcp-server
- Create Virtual Environment
python -m venv venv
source venv/bin/activate # On Windows: venv\Scripts\activate
- Install Dependencies
pip install -r requirements.txt
- Setup Database
-- Connect to PostgreSQL
psql -U postgres
-- Create database
CREATE DATABASE airline_delays_db;
-- Connect to database
\c airline_delays_db
-- Enable pgvector extension (if using vector operations)
CREATE EXTENSION IF N
Tools (6)
authenticate_passengerSecure passenger login and session management using PNR or frequent flyer details.get_flight_statusRetrieve real-time flight status, gate details, and delay information.analyze_sentimentDetect passenger sentiment to recommend appropriate communication tones.get_engagement_activitiesProvide delay-appropriate entertainment activities based on duration.get_itinerary_recommendationsGenerate personalized airport restaurant and destination activity recommendations.transfer_to_humanEscalate complex issues to human specialists with full conversation context.Environment Variables
OPENAI_API_KEYrequiredAPI key for LLM-powered emotional intelligence and analysisDATABASE_URLrequiredConnection string for the PostgreSQL databaseConfiguration
claude_desktop_config.json
{"mcpServers": {"airline-delays": {"command": "python", "args": ["/path/to/airline-delays-mcp-server/main.py"], "env": {"OPENAI_API_KEY": "your-key-here"}}}}Try it
→My flight is delayed by 3 hours, what entertainment activities can you suggest?
→Check the status of flight AI-501 and see if there are any rebooking options.
→I am very frustrated with this delay, please help me find a quiet place to eat at the airport.
→Escalate my current issue to a human agent as I need to reach my destination for an urgent meeting.