How MCP Could Simplify AI and SaaS Integrations for Teams

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.

Firstly, what is MCP?

The Model Context Protocol (MCP) is an open standard that helps developers connect AI systems to data sources like content repositories and business tools. It simplifies integrations by using a single protocol, making it easier for AI to access relevant data.

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 and 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, ...)

MCP Marketplace & 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.

In conclusion...

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 Protocol on top to act as a bridge? I hope not.

But in the long run there will be one/multiple standards (maybe its 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.

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