Using MCP in a Business Context

MCP (Model Context Protocol) is getting tons of attention on the tech side.

To really understand its impact, we need to see how Tool Calling Agents can make a big difference for companies and especially their non-tech employees in the future.

But first, here's a complete walkthrough of MCP Model Context Protocol to understand MCP ( + how to build your first Server in Cursor):

The Problem with Scattered Tool Use

Most AI interactions today happen separately. You ask one AI tool for one specific thing. And honestly, even this isn't common yet. Usually, people still have to open multiple tabs or tools, paste data back and forth, and manually search through apps like Slack, HubSpot, or GitHub.

And that's messy. Data and answers get scattered across different platforms. This leads to confusion and bigger expenses.

 So, right now, working with multiple isolated AI tools is slow, expensive, and frustrating.

Natural Language + One Chat App

That's why ChatGPT or Claude feel easy. Multiple Saas Tools (CRM, ATS, CMS, name it!) or multiple AI assistants add a lot of complexity. 

The goal should be a single chat that calls them silently. This isn't MCP's main job, although it can lead in this direction as it handles all these tool connections in a smooth way. (See Claude Desktop)

Save time

In a company setting, this means no complicated training for individual apps, no login or password headaches, and none of the usual problems these tools cause.

Users don't even need to know where the data comes from. They just get answers from everywhere.

Save money

Why not rely on basic APIs and skip extra layers?

When all tools speak the same language (JSON-RPC 2.0) its easier to swap Slack for MS Teams or Jira to Linear. 

In "older" setups, you have to take care of the integraton. (Auth, rate limits, error handling, ...)

Control and Privacy

There are already directories where users can discover and install MCP servers for various tasks. For example, Cline's MCP Marketplace allows users to browse and install MCP servers with a single click, simplifying the setup process.

You can host your MCP Server data directly on your own server or local hardware. This can make GDPR compliance easier for companies. OpenAI on the other hand processes data externally in the cloud.

How MCP Works in a Team Setting

To understand how MCP plays out in real-world use, here’s an example of a team structure leveraging this protocol:

End users
Are the people using the AI app to get work done. They might ask about an invoice or get help with a task. They only see the chat or app interface. They do not need to know how the system works.

AI app developers
Build the assistant and make it MCP compatible. They add an MCP client inside the app. This lets it talk to one or more MCP servers and use external tools or data. They even use MCP Server themself for developing. 

Tool or API developers
Build the MCP servers. These connect real services to the AI. For example, someone might build an MCP server for a company’s internal database. Or someone might create one for a public API.

Enterprise
Integrate MCP into their infra, ensure security, and connect internal systems like CRMs or databases to the AI.

This setup lets the AI assistant pick the right tool when needed. The MCP server handles the call, connects to the external service, and sends back the result in a simple format.

The Benefit?

The benefit here is clear roles. AI app developers do not need to learn every API in detail. Tool developers do not need to worry how the AI will use their server. They both follow the same protocol.
It works like the web, where everything uses HTTP and JSON. With MCP, JSON RPC is the shared language that connects tools and AI.

Where MCP Stands Now

A blessing for end users and a curse for developers?

MCP has its problems (e.g. stateful vs. stateless). Especially developers (like me) prefer direct solutions and want to keep things simple.

Another drawback is that much of what I've described can only be done in Claude's desktop and code editors (Cursor, Windsurf, Cline). So there is a risk that this protocol will remain in the Anthropic universe and other vendors will never support it.

So what is the result?

Multiple protocols where we need another Procotol on top to act as a bridge? I hope not. 

But in the long run there will be one/multiple standards (maybe it's MCP, maybe something else) that will bring this to the enterprise. And we developers will implement or build products and service those solutions.

 So companies and developers will inevitably have to deal with it. The pros (if it all works) outweigh the cons immensely.

 And it's still a very young protocol, so don't curse it all, make the best of it, try it out and fail. It's all about experience. Just like any other technology.

 First mover advantage.