{"repo":"Azure-Samples/azure-ai-travel-agents","free":true,"listed":false,"github":"https://github.com/Azure-Samples/azure-ai-travel-agents","clone":"git clone https://github.com/Azure-Samples/azure-ai-travel-agents.git","description":"A robust enterprise application sample (deployed on ACA) that leverages MCP and multiple AI agents orchestrated by Langchain.js, Llamaindex.TS and Microsoft Agent Framework.","language":"TypeScript","stars":477,"topics":["agents","ai","azure","container","llamaindex","aspire","dotnet","java","javascript","mcp"],"license":"MIT","category":"ai-agents","readme_excerpt":"Agents and MCP Orchestration with Langchain.js, LlamaIndex.TS, and Microsoft Agent Framework! :star: To stay updated and get notified about changes, star this repo on GitHub! Overview • Architecture • Features • Preview locally FOR FREE • Cost estimation • Join the Community Overview The AI Travel Agents is a modular reference application that leverages multiple AI agents to enhance travel agency operations. The application demonstrates how LangChain.js , LlamaIndex.TS , and Microsoft Agent Framework can orchestrate multiple AI agents to assist employees in handling customer queries, providing destination recommendations, and planning itineraries. Multiple MCP (Model Context Protocol) servers, built with Python, Node.js, Java and .NET , are used to provide various tools and services to the agents, enabling them to work together seamlessly. Agent Name Purpose -------------------------------- ----------------------------------------------------------------------------------------------------------------------------- Customer Query Understanding Extracts key preferences from customer inquiries. Destination Recommendation Suggests destinations based on customer preferences. Itinerary Planning Creates a detailed itinerary and travel plan. Echo Ping Echoes back any received input (used as an MCP server example). High-Level Architecture The architecture of the AI Travel Agents application is designed to be modular and scalable: - All components are containerized using Docker so that","default_branch":null,"files":null,"tree":[],"storefront":"/r/Azure-Samples","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/Azure-Samples/azure-ai-travel-agents/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}