Build a Real-World Multi-Agent AI App with MCP + LangGraph | Part 2

In this video, we extend our Multi-Agent Travel Planning System built with LangGraph by integrating MCP (Model Context Protocol) servers for real-time flight and weather information.

📌GitHub Code: https://github.com/codewithaarohi/AI-Travel-Planning-App-using-LangGraph-and-MCP

📌 Part 1 Project Repository:
https://github.com/codewithaarohi/AI-Travel-Planning-System-using-LangGraph

📌 Part 1 Project Video:
https://youtu.be/_5XF5CCnbDk

📌 Learn about Model Context Protocol (MCP) - https://youtu.be/zA3RirPFFsU

📌 AviationStack MCP Repository:
https://github.com/Pradumnasaraf/aviationstack-mcp

📌 Tavily MCP Documentation:
https://docs.tavily.com/documentation/mcp
You will learn how to:
✅ Connect LangGraph Agents with MCP Servers
✅ Integrate AviationStack MCP Server
✅ Build a Weather MCP Server
✅ Use Real-Time Flight Data in AI Agents
✅ Use Real-Time Weather Data in AI Agents
✅ Add Long-Term Memory using PostgreSQL
✅ Create a Multi-Agent Travel Planning System
✅ Run the application in Terminal and Streamlit

By the end of this tutorial, you'll have a production-style Agentic AI application that combines:
• LangGraph
• MCP (Model Context Protocol)
• PostgreSQL Memory
• Tavily Search
• AviationStack API
• OpenWeatherMap API
• Streamlit UI
#MCP #LangGraph #AgenticAI #AIAgents #MultiAgentSystems #Python #GenerativeAI #LLM #AIEngineering #TravelAI

📸 Follow me on Instagram: @codewithaarohi
🔗 https://www.instagram.com/codewithaarohi/

📧 You can also reach me at: aarohisingla1987@gmail.com

Видео Build a Real-World Multi-Agent AI App with MCP + LangGraph | Part 2 канала Code With Aarohi