đ¤ Where MCP Fits in Hospitality Tech
âĄď¸ What is MCP?
MCP stands for Model Context Protocol. It defines a common protocol for large language models (LLMs, like GPT) to communicate with external tools, APIs, and data sources. Think of it as âdrivers for LLMsâ â instead of every developer writing one-off adapters, MCP standardizes the interface. In hospitality, that means replacing countless custom integrations with a single adapter layer.
đŻ Connecting AI to Core Systems
With MCP, an AI assistant could securely and consistently connect to:
đź PMS (Property Management System) â reservations, guest profiles, room status
đź RMS (Revenue Management System) â pricing, occupancy, demand forecasts
đź CRS / Channel Manager â availability and distribution to OTAs
đź POS (restaurant/spa) â spend data, guest preferences
đź CRM / Guest Engagement Tools â loyalty programs, past stay history
đŻ Example AI Use Cases via MCP
1ď¸âŁ AI Concierge
Pull real-time availability from PMS
Combine with spa POS slots
Instantly answer a guest request: âCan I book a couples massage at 5pm and add late checkout tomorrow?â
2ď¸âŁ Revenue Managerâs Copilot
Fetch pickup data from RMS, competitor rates from a Rate Shopper, and local event data
Suggest: âIncrease Saturday rates by 12% â high suite pickup plus a local concert.â
đ Whatâs Next?
The promise of MCP in hospitality is clear: standardized, secure, AI-ready integrations across a fragmented tech stack.
But this is just the beginning. Beyond guest service and revenue, MCP could unlock:
Smarter operations assistants (housekeeping, maintenance, F&B)
Personalized guest messaging driven by real-time data
Unified dashboards for owners and GMs, blending insights from every system
đ What other use cases do you see for MCP in hospitality?

