MCP in Travel: How AI Is Reshaping Travel Commerce

In travel, we are all excited about the potential of AI agents to provide an improved user experience. Specifically, agentic travel commerce promises a future where AI can understand our intent, propose a highly relevant trip and execute booking and payment.

It’s an exciting vision, informed by one of the most significant technology advances of modern times. As the market develops, it is important to distinguish between easier connectivity and the broader capabilities required to make agentic travel work in practice.

The purpose of this article is to explain the role of Model Context Protocol (MCP) in travel distribution, what it enables and where the wider complexity of travel commerce remains.

MCP provides a common standard for AI agents to connect and interact with data sources.

The standard has been widely adopted as a way for data owners to expose information and capabilities in a form AI agents can readily use.

A hotel or airline can use an MCP server, for example, to make selected services from its underlying systems and APIs discoverable to an AI agent. MCP is a useful and well-designed protocol, but it does not itself provide intelligence, decision-making, orchestration or automation. The value ultimately depends on the content, business logic and operational capabilities made available through it.

MCP is one part of a broader and rapidly evolving protocol landscape. It provides a standardized way for AI applications to discover and use data and capabilities, while other emerging models are being developed to support additional elements of agentic communication and commerce.

Commerce-oriented protocols such as Universal Commerce Protocol (UCP) may support additional parts of the shopping and transaction journey. These approaches may ultimately prove complementary rather than interchangeable. Amadeus is working with Google and other industry participants to help develop UCP for lodging and explore how emerging commerce standards can reflect the specific requirements of travel.

The industry has already moved beyond theoretical discussion. MCP-based travel solutions are beginning to support live use cases, from conversational flight search to booking and selected servicing workflows. These developments are valuable evidence that standardized agent connectivity can accelerate innovation, and they should be recognized as meaningful progress. At the same time, the existence of a live MCP connection does not by itself demonstrate that the broader requirements of travel commerce have been solved across content, providers, journeys and servicing scenarios.

As MCP makes it easier for travel providers to expose capabilities to AI agents, an important question is whether those agents will increasingly search and book directly with individual providers, reducing the need for aggregation and distribution services. This is a credible scenario to examine, but connectivity alone does not address the wider requirements of travel commerce.

MCP simplifies connectivity. It does not simplify travel distribution. Connecting an AI assistant to a single airline is fundamentally different from enabling it to efficiently search, compare, book and service travel across the market.

It can be relatively straightforward for a provider with an existing API to make capabilities accessible through MCP. But easier connectivity does not remove the underlying complexity of travel commerce. Here’s why:

• Business logic and fulfilment

While an AI agent might be able to complete a simple booking via an MCP connection with an airline, a flight reservation involves complex business logic in areas like ancillary selection, seat maps, baggage rules, regulatory compliance, interline partnerships and dynamic pricing, complex logic that sits within the underlying travel technology and systems of record.

MCP can provide a means of connecting to capabilities; it does not itself provide this business logic.

Travel purchases must also support servicing requests like ticket changes, adding or removing services, cancellations and refunds. Travel commerce is about far more than the initial search, with an ongoing requirement to reliably execute complex changes within systems of record. The industry requires a single source of truth.

In other words, an AI assistant may become the interface through which a traveler makes a request, but the underlying transaction still needs to be priced, executed, fulfilled, recorded and serviced.

• Cost

If each AI agent were to consult each provider directly via MCP, it would add significant additional infrastructure, processing and cost pressure on both providers and AI companies.

Today, a booking made via Amadeus using traditional EDIFACT connectivity requires an average of 4,000 background transactions, while a New Distribution Capability booking requires closer to 20,000.

Should AI agents begin to query provider systems at scale, this look-to-book ratio would rise to prohibitive levels, with providers incurring significant additional IT costs simply to make their offers available.

Similarly, AI companies operating the Large Language Models (LLMs) that power AI agents would also be exposed to additional costs.

LLM infrastructure requires significant computing resources. It simply isn’t efficient to conduct a travel search by sending an AI agent over the web to query hundreds of providers. Instead, aggregation remains vital. Replacing a direct interaction with one provider is very different from replacing the aggregation and comparison capabilities of a distribution platform.

• Latency and search quality

Travelers expect fast, accurate search results that display the most competitive pricing options from the whole of the market, with very low latency.

The more providers an AI assistant needs to query individually to provide comprehensive comparison shopping, the greater the cost, complexity and latency involved. Aggregation solves this by providing broad, harmonized content through a common infrastructure.

By contrast, Amadeus answers 3B flight search requests every day and is able to return relevant, up-to-date dynamic prices at low latency. This capability is reinforced by our role as a Passenger Service System (PSS) provider to a significant number of airlines, giving us close integration with the operational systems where availability, schedules, fares and servicing information are maintained. This helps improve the accuracy and freshness of the content we provide to travel sellers and AI-driven channels.

MCP will play an important role in agentic travel commerce, and Amadeus supports its adoption as a valuable industry development. Live implementations across the industry are already demonstrating how MCP can make travel capabilities easier for AI applications to discover and use. But speed to expose an interface is only one measure of progress. The more demanding test is whether an agent can reliably complete a real journey across search, comparison, booking, payment and servicing, while respecting supplier rules and maintaining an accurate system of record.

Many of the underlying capabilities required to do this already operate through Amadeus APIs and integrations at global scale. Our focus is therefore not simply on adding a protocol layer, but on making our travel content, business logic and execution capabilities accessible to AI-driven channels in a way that delivers measurable customer value. This includes our investments in intelligent search, booking and servicing, agent-to-agent communication and emerging commerce protocols. As MCP adoption grows, we will support it alongside the wider capabilities needed to move from an AI demonstration to reliable travel commerce.

Long-term differentiation will come from the travel intelligence, content, workflows and business capabilities exposed through these interfaces. For Amadeus, that means enabling access to broad, aggregated travel content, accurate and up-to-date pricing, low-latency search, deeply integrated business logic and advanced servicing capabilities, while helping shield provider systems from excessive agentic search volumes.

Technology and industry structures evolve, and it would be wrong to assume that today's distribution model will remain unchanged. The more useful question is what would need to happen for direct agentic commerce to replicate the value aggregation provides today.

That would require several significant developments. Airlines would need to make transactable capabilities broadly available to third-party AI agents, at a scale and on commercial terms that support widespread comparison shopping.

This is not simply a technical decision: providers must also decide which capabilities they want to expose to third-party agents, under what commercial conditions, and at what level of search volume.

AI-driven channels would also need to reliably manage the complexity of multi-airline journeys, including interline ticketing and settlement. And they would need to address what happens after the initial booking, from changes and cancellations to refunds and disruption management, while maintaining the reliable systems of record, accountability and servicing that travel requires.

We do not see these capabilities operating at the breadth, reliability and scale required to replace aggregation today. As they evolve, Amadeus is evolving too, both through our distribution capabilities and through the technology that supports airlines' own operations and direct channels.

The next phase of agentic travel should therefore be judged by operational evidence rather than protocol availability alone: the breadth of content available, the number and complexity of transactions completed, response times, servicing completion, exception handling and the level of human intervention required. Early deployments are important, but the long-term benchmark will be whether these capabilities can operate reliably across providers, content sources and the full lifecycle of a trip.

Amadeus is uniquely positioned to orchestrate the AI-enabled travel ecosystem, connecting suppliers, sellers and AI assistants to trusted, dynamic travel data at scale, in a neutral, secure and responsible way.

When an AI assistant moves from recommending a journey to booking, paying and servicing it, trust becomes operational. The underlying systems must preserve accurate availability and pricing, protect traveler data, apply the relevant commercial and regulatory rules, and maintain a reliable record of every transaction. Common protocols can improve connectivity, but they do not replace the governance, resilience and accountability required to support travel operations at scale.

We are closely collaborating with major AI companies, including Microsoft, Google and Anthropic, to determine how best to bring the benefits of agentic commerce to travelers, providers and the broader industry.

We are harnessing our position as a trusted system of record in travel to connect AI assistants and other agents owned by airlines, travel sellers and other travel companies with trusted, dynamic travel data (from individual or multiple suppliers), in a secure and responsible way.

With global scale, deeply connected business logic and a one-to-many value proposition, we can help AI assistants efficiently connect to a diverse range of travel content while providing similar value to providers seeking to broaden their ecosystem of content for air, hotel, mobility and more.

AI augments the Amadeus platform and, as travel’s neutral execution layer, we recognize that we have a critical role to play to reliably process the transactions that underpin AI recommendations.

The interface through which travelers search and book may change; the underlying complexity of travel commerce does not disappear.

Our opportunity is to make that complexity invisible, connecting new AI interfaces with the content, technology, business logic and execution capabilities that make travel work.

As agentic commerce develops, we believe Amadeus can play an important role in turning AI-powered recommendations into reliable, real-world travel transactions at scale.