AI Travel Planner 是一个基于 Spring Boot + Spring AI 的后端与 Vue 3 + Vite 的前端组合项目，面向智能旅游场景，提供 智能行程规划、多模态问答与个性化推荐 能力。 系统集成了 MCP (Model Context Protocol) 工具链，支持从 自然语言理解 → RAG (Retrieval-Augmented Generation) → 多 Agent 协同 → 个性化生成 的完整 AI 应用流程。同时配套 CSV 向量化预处理脚本，实现高效的数据清洗、向量化与检索。

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An enterprise-grade travel planning intelligent agent system built by Agno framework. Integrating advanced functionalities including MCP, Skills, Memory, Knowledge Bases, Agent Teams, and Workflows.

This agent A New AI Agent Every Day! Series Day 2/21 - On-the-Road Museum Travel Agent's 🏛️ 🎉This agent that will make your travels richer using GoogleMaps MCP! 🚗✨ Shows you the must-visit museums in other cities you will pass through during your trip between two cities 🗺️

Gen AI Travel Agent with Multi-MCP Integration: Real-time flight search, Airbnb booking, Google Maps navigation, and comprehensive travel planning using Agno, OpenAI, SerpAPI, and RAG technology for intelligent itinerary generation.

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Agente de IA que utiliza um MCP para ler uma API sobre tipos de mecanismos de viagens interestelares em obras de ficção científica

Time-travel debugging for MCP agents: record, replay, and step through tool calls.

AI travel assistant that uses the Airbnb MCP to query accommodation data and answer user travel queries via agentic workflows.

A production-ready, framework-free Agentic Workflow for travel planning built with Python and the Model Context Protocol (MCP).

This agent for Analyzing traffic density, suggesting alternative routes, and estimating travel times with Google Maps MCP. 🚗🛣️

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Revolutionary AI-powered travel planning system with multi-agent coordination, personality-driven recommendations, interactive maps, and climate-smart planning. Features 5 specialized AI agents, real-time data integration, voice assistant, and comprehensive analytics for personalized travel experiences.

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Multi Agent Travel Chat Service System Using Langgraph, A2A, MCP Frameworks

MCP server for agent-controlled context checkpointing and time travel - like Memento for Claude agents

An intelligent travel-planning assistant built with LangChain and Agent workflows. It supports real-time travel information retrieval via MCP (Model Context Protocol) tool-calling, including transportation, flights, weather, and more.

Local-first travel planning workspace with an AI copilot. Plan trips day by day — hotels, activities, costs — with a LangChain agent and MCP server for agentic access via Claude Code.

A web application that uses agentic AI to help communicate and find travel destinations/tourism spots and a weather update of the location. The agent uses MCP to access the tools.

Streamlit-based AI travel planner using multi-agent MCP architecture. Integrates Airbnb MCP for real-time stays and Google Maps MCP for precise distances. Delivers detailed itineraries with costs, buffer times, weather, dining, and attractions, plus calendar export and budget insights.

An intelligent trip planning application built with AutoGen agents and Model Context Protocol (MCP) server. This application uses AI agents to create personalized travel itineraries based on user preferences and real-time attraction data.

Step-by-step local setup and integration guide for Galaxium Travels, watsonx Orchestrate Developer Edition, MCP, and IBM Bob to prepare and build an AI travel booking agent.

Successfully developed a Travel Planner Assistant powered by LangGraph and MCP, integrating real-time flights, hotels, weather, places, and timezone tools. Features modular MCP servers, OpenAI agent orchestration, and a Streamlit UI for end-to-end trip planning.

A multi-agent trip planning application built with Google ADK, MCP servers, and A2A design patterns. Agents collaborate to handle destination research, itinerary generation, and hotel/flight booking research, demonstrating orchestration of tool-using LLMs in a real-world travel scenario.

This is a multi-agent AI system built using LangGraph and LangChain that orchestrates specialized agents for travel planning, expense tracking, and document-based reasoning (RAG). The system integrates tool-augmented reasoning via MCP, persistent conversation memory using PostgreSQL, and a FastAPI backend for real-time streaming interactions.

Flight Search MCP Server - Real-time flight data via Model Context Protocol. Search flights, airports, and price trends using SerpAPI. Perfect for AI travel agents and planning applications. Supports JSON-RPC with comprehensive flight information including prices, airlines, booking links, and airport details.

To address the issues of traditional travel inquiry systems, such as their single functionality, fragmented services, and cumbersome interaction, a distributed multi-Agent collaboration system is built based on the A2A and MCP protocols, enabling one-stop intelligent inquiry for information such as weather, transportation, and ticketing.

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