AI is changing business travel quickly. New assistants, platforms, and analytics tools promise faster answers and simpler experiences.
But for AI to provide useful recommendations, it needs access to the information that sits across a travel program’s many systems and data sources. Without that context, even the most advanced models can only offer generic responses. That is where Model Context Protocol (MCP) comes in. At its core, MCP addresses a challenge that travel managers know well: disconnected data.
What is an MCP server, and why does it matter in business travel?
MCP has become one of the most talked-about technologies in the rapidly evolving AI landscape. It’s especially relevant in business travel because accessing a complete view of your travel program often requires information from multiple sources. Booking data may sit in one system, expense data in another, and policy, sustainability and supplier information somewhere else entirely. MCP provides a common framework for AI applications to connect these sources together, creating opportunities for faster analysis, clearer policy guidance and more streamlined traveler experiences.
For example, Advito has long brought together fragmented travel data through solutions like Total Trip Insights, consolidating information from agency, expense and supplier sources into a more complete view of program performance. MCP builds on connected data foundation like this by making it easier for AI applications to access the right information or analytical capability in response to a specific question. Instead of replacing the work required to consolidate and prepare reliable data, MCP can make that trusted information easier to interact with and use.
How does an MCP server work?
Behind the scenes, an MCP server serves to expose three types of capabilities to an AI application: which information it can access, actions it can perform (e.g. calculations) and guidance or prompts that help it use those capabilities appropriately. The technical architecture has several parts, but the user experience can be simple. Imagine one of your travel technology providers launches an AI assistant that can answer questions using information from your travel policy, booking data and expense data all at once. For example, you might ask: Within which markets did our hotel spend exceed the city rate caps last quarter?
- The application determines which information it needs to answer the question.
- It sends structured requests through an MCP server.
- The MCP server accesses approved sources, such as travel policy documents, booking data and expense data, based on the permissions configured by the organization.
- The AI application combines that information and returns a response.
While the MCP server isn’t analyzing the data itself, it helps the AI application access and use relevant information across multiple approved sources, giving it the context needed to provide a more meaningful answer.
MCP servers vs. APIs: What’s the difference?
You may be thinking this sounds very similar to application programming interfaces, or APIs, the travel industry has used for years. They are related, but they serve different purposes. An API defines how one software system requests data or actions from another. MCP gives AI applications a common way to discover and use approved data, tools and capabilities from multiple sources.
Key takeaway: APIs are not going away. In many cases, an MCP server may use existing APIs behind the scenes. The difference is that MCP provides a more consistent framework for making those capabilities available to AI.
Why is MCP important for AI?
Generative AI is good at working with language, but a general model does not automatically know your company’s travel policy, supplier agreements, booking activity or sustainability goals. To give a relevant answer, it needs access to trusted context.
MCP creates a standard way to provide that context. Because MCP uses a common framework, organizations are beginning to use it to add new AI experiences or connect new capabilities without rebuilding every integration from scratch. It also gives technology teams clearer boundaries around what each server exposes.
Keep in mind, standardization alone does not make an AI workflow secure or accurate. Organizations still need to control identity, authorization, data access, validation, monitoring and human approvals.
Why should travel managers care about MCP servers?
For travel managers, the value of MCP is that it creates opportunities for AI to work across multiple sources of travel data, helping teams answer questions, identify trends and take action more quickly within the context of their whole travel program.
The potential for MCP in business travel extends across the entire travel program. It could help AI support policy compliance, supplier performance, cost control, and strategic decision-making. It is not just about answering traveler questions more effectively. It is about giving travel teams easier access to the information they need to manage their programs and make informed decisions.
Importantly, that doesn’t mean replacing the role of the travel team. The real value comes from helping travel managers spend less time gathering and reconciling information, and more time interpreting insights, identifying opportunities and driving program improvements.
How can organizations use MCP responsibly?
Like any emerging technology, better connectivity alone does not guarantee better outcomes. While MCP can make it easier for AI to access and work with information across multiple systems, the value it delivers will ultimately depend on the quality of the data and the controls and governance surrounding it.
Travel managers don’t need to understand the technical details of how an MCP server is built, but they should understand the key considerations that can influence outcomes:
- Access controls: Who can view, use or act on information retrieved through connected systems?
- Governance: What oversight exists to ensure AI is operating within company policies and approved workflows?
- AI hallucinations: Even with access to better information, AI can still generate inaccurate or misleading responses if outputs are not validated.
- Security: Every new connection creates potential risk, making authentication, monitoring and permissions critical.
MCP may simplify how systems connect, but it doesn’t remove the need for strong governance. Organizations still need clear policies, security controls and human oversight to ensure AI is applied responsibly. AI should support decision-making, not replace the experience and judgment required to make the right decisions.
What does the future look like?
As business travel becomes increasingly AI-driven, MCP could provide a common framework for connecting AI applications to approved capabilities across booking, expense, duty of care, sustainability and business intelligence environments. Instead of moving between platforms to search for information, travel managers may be able to ask a question and bring together relevant context from across the program.
As MCP continues to get integrated into more systems, it will continue making travel program data easier to access, understand and act on. Organizations that strengthen their data foundations, governance and AI readiness today will be better prepared to take advantage of new capabilities as they emerge.
To learn more about how Advito is integrating AI-powered capabilities across our solutions to deliver sharper insights and more informed travel program decisions, contact our team.
