MCPs: Why Should Your Company Care About Them?

As the use of large language models (LLMs) accelerates across industries, we’re entering a new era of model interconnectivity—one where isolated systems aren’t enough. To unlock the full potential of AI, we need protocols that let LLMs access knowledge, tools, and services across domains. That’s where Model Context Protocols (MCPs) come in.

What Are MCPs?

Model Context Protocols, or MCPs, are a new interoperability layer for LLMs. Much like APIs allow software applications to communicate with each other, MCPs allow language models to query, retrieve, and act on structured information from external services—in real time.

Think of them as APIs, but designed specifically for how LLMs interact with the world. MCPs let models enrich their context with facts, data, and capabilities from remote sources. Rather than retraining or hardcoding everything into the model, you let it fetch what it needs. You can think of an MCP like a digital menu at a restaurant where you can both see what is available to eat AND actually place the order as well. This is the incredible power that will be unlocked by MCPs.

In a world where models are context-hungry but memory-limited, MCPs offer a powerful way to keep them light, adaptable, and well-informed.

Why MCPs Matter to Your Company

If your business uses or builds LLM-based applications, MCPs are more than just a buzzword—they could be a strategic advantage. Although we are still in the early innings of tooling and adoption, the MCP standard is designed to be interoperable and model agnostic. Here are three key ways to benefit from them:

1. Make Your LLMs Smarter by connecting to Public MCP Servers

Many organizations are beginning to expose their capabilities via public MCP servers—search, finance data, geolocation, health lookups, or even product catalogs.

Companies using LLMs can now integrate these sources directly into their applications. Instead of depending only on what’s in the model’s training data, your LLM can query a trusted MCP server at runtime, pulling fresh, structured results—securely and efficiently.

Example: An LLM that answers insurance questions could use a public MCP server to pull real-time rate tables, underwriting guidelines, or claim history lookups.

2. Expose Your Services as MCPs for Others to Use

If your company provides APIs or services to external developers or clients, you should consider offering an MCP interface in parallel.

This opens your business to a new channel: LLMs themselves. Just like APIs became a standard way for apps to integrate, MCPs may become the standard way for LLMs to plug into useful services.

Imagine being the source LLMs turn to for price quotes, eligibility checks, document templates, or customer service workflows—all through a structured, context-friendly protocol. There is a strategic first mover advantage for companies who move quickly to expose their services as MCPs.

3. Connect Internal LLMs to Shared Services via MCP

For companies running multiple LLM-based systems, a hidden opportunity is to enable key internal APIs as MCP servers. This allows you to reuse trusted tools across LLMs without duplicating logic.

Think of MCPs as a “service bus” for models: they let you compose applications with models that pull from shared knowledge stores, policy engines, or data transformation pipelines.

The result: less duplication, more standardization, and easier compliance monitoring.

Final Thoughts

MCPs represent a subtle but important shift—from static models to connected, composable systems. Companies that embrace this shift early will benefit from faster development, smarter models, and new integration surfaces for customers and partners.

If your company is thinking about how to get the most out of LLMs, MCPs are worth your attention—not just as a technical curiosity, but as a real architectural tool for competitive advantage.

Curious how MCPs might fit into your architecture? At Arica, we help our clients pragmatically deploy new technologies and would enjoy the opportunity to connect with you and support your Generative AI future. Please contact us at don@arica.co or jim@arica.co to connect live.