Why Every Product Should Have a Dedicated MCP Server
A practical look at why Model Context Protocol (MCP) is about to become the essential bridge between AI agents and real-world applications. If you want your product to be usable by the next generation of LLM powered tools like Claude Code or the upcoming GPT agents setting up a dedicated MCP server is the best way to future-proof your stack and stand out. This article breaks down what MCP actually is, why it matters right now, and how early adopters can leapfrog the competition by building for the new AI-native ecosystem.
What is MCP?
MCP stands for Model Context Protocol. It's an open protocol created by Anthropic, designed to make products work seamlessly with AI agents. Picture this: your AI agent wants to interact with your GitHub repo. That is only possible because GitHub already has its own MCP Server running in the background.
An MCP Server is the code that lives on the product side and exposes it to MCP Clients. These clients live inside AI agents or chat apps. The owner or developer of the agent integrates the client, giving the agent the ability to "speak" to the server and actually understand how to interact with the product. Or, as Anthropic puts it:
"MCP is an open protocol that standardizes how applications provide context to LLMs. Think of MCP like a USB-C port for AI applications. Just as USB-C provides a standardized way to connect your devices to various peripherals and accessories, MCP provides a standardized way to connect AI models to different data sources and tools."
Why every product should have it
Adding an MCP Server to your product now, while most companies have not even started thinking about it, puts you ahead of the game. This is how you make your product AI-native before it becomes the industry norm, not just an extra feature. Say you're running a booking website and you add an MCP Server that lets agents browse available rooms and make reservations for users.
When someone is chatting with their favorite AI assistant about travel plans, the assistant can actually book a room on your platform directly. No extra steps, no lost users, no competing with platforms that are not ready for agents. The AI plugs into your MCP Server and your product becomes the obvious choice.
The future of MCP
Products everywhere are starting to ship with their own MCP Servers. Cloudflare, Gmail, GitHub, and others are getting on board. At the same time, more AI apps are rolling out MCP Clients, with OpenAI planning to put MCP Clients directly into ChatGPT. If you want to stay ahead, this is the moment to make your product part of the next generation, while most are still catching up.