Understanding MCP: The Future of AI orchestration

The assortment of backend data source tools, frontend solutions, LLM models, AI agents etc., is a true smorgasbord of options for any company. 

You can get exactly what you need for your tech stack, and that’s absolutely awesome. Composable architecture FTW! 

But it also leaves developers and marketeers with a pretty intricate web of data that can be a bit overwhelming to manage if, for instance, you want to utilize (your own) data to enhance the efficiency and precision of AI models.

And that’s where the Model Context Protocol (MCP) comes in. MCP is a game-changer in data orchestration and offers a streamlined approach to integrating AI models with various data sources or other AI models, enabling seamless communication and enhanced efficiency. 

Understanding Model Context Protocols 

MCP is designed to make AI systems more efficient and scalable by replacing the need for multiple custom architectures and technologies with a standardised, reliable protocol. This not only simplifies the process but also enhances the overall performance of AI systems. 

Just think of how confusing, time-consuming, and downright frustrating it is when every hardware device needs a different type of cable or adapter. It’s the same for data sources and AI – and that’s the pain that MCP fixes. MCP refers to itself as the USB standard of AI models, introducing a unified interface for all purposes. 

MCP is a universal, standardised way to connect AI models with any data source or tool without the hassle of custom integrations. It enables any AI model to communicate with any tool and data source seamlessly. There is only one MCP standard, and everyone adheres to this same set of rules and specifications.

Okay, so now we pretty much grasp the general concepts of MCP and the overall use case (I hope). But what are the business benefits? Read our blogpost 👉 Accelerating business growth with MCP.

So, what now?

A lot of us will probably have a few questions. Is the MCP hype justified, or is it just another tool? Will MCP become a prerequisite for exposing data to and between AI systems? Will MCP win the VHS battle to become the new standard of connecting AI models and data?

MCP is still in its early stages, but the widespread support strongly indicates that MCP could become the next big thing. For instance, tech giants like Google, Microsoft, and Amazon are investing heavily in MCP. They are integrating MCP into all relevant services of their ecosystems to streamline data orchestration and improve AI capabilities. This adoption by major players is a strong indicator of MCP's potential to revolutionise the way we handle data and AI integrations. <link>

But yeah… Tech and marketing are both subjects filled to the brim with buzzwords and “ground-breaking new terminology” that will “completely change the way we work”. Sometimes these big announcements end up being just a buzz … They didn’t truly catch on. 

BUT. We really do expect MCP to gain massive momentum. 🤞