A comprehensive travel planning copilot that provides geographic data, weather forecasts, transportation details, currency exchange rates, and contextual content to create personalized travel experiences. Enables users to plan itineraries, check real-time conditions, and gather inspirational content for destinations.
Search 70,000+ cruise voyages, 678 ships, and 62 cruise lines worldwide. No API key needed, no
installation required — just paste the URL. Includes RAG-powered knowledge search for ship
dining, facilities, cabins, and port guides. 30 languages supported.
Enables extracting explicitly stated contract metadata, clauses, and obligations from user-supplied contract text without storing or modifying the data.
Enables AI agents to autonomously search, pay, and book travel by integrating Travala's travel inventory with FurlPay's payment rails, supporting both crypto-native and legacy payment methods.
Provides AI agents with a structured API for travel planning, enabling them to read trip data, search places, calculate routes, and create/validate itinerary change proposals that require explicit human approval before being applied.
A production-ready MCP server for intelligent travel planning that integrates 16 tools, live APIs, and a gamification system to help users plan trips, track expenses, and discover events.
Exposes tools for retrieving member profiles and personalized travel recommendations with multi-tenant partner rule enforcement, enabling AI agents to respect business constraints like caps and exclusions.
Enables searching tours on eto.travel using browser automation via Playwright. Supports finding a single tour or a categorized selection (budget, optimal, premium) based on filters like destination, departure city, nights, and month.
Enables AI agents to fetch personalized travel recommendations for loyalty program members while enforcing partner-specific business rules such as category exclusions and recommendation caps. Exposes MCP tools over Streamable HTTP, with a REST endpoint, CLI, and frontend for end-to-end demonstration.