MCP: The API 2.0?

How to combine a chatbot with your data or tools.

In the previous digest, I mentioned that the model context protocol is gaining momentum. And it doesn't look like a temporary trend but an essential part of the AI industry. If I may say so, it is like “API 2.0.”

Using this platform, creators combine existing tools with chatbots to build practical solutions. We haven't yet had an easier way to create new use cases without advanced skills.

And it synergizes perfectly with the idea of vibe coding.

In this post:

• What is Model Context Protocol (In Simple Words)

• Five Case Studies You Can Check Right Now

• How to Use Set up Your First MCP

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What Is MCP?

This is how Claude can work with a combination of Perplexity via MCP.

So, to avoid overwhelming you with technical details (you can look up a meticulous definition here), let's keep it short and simple.

Model Context Protocol (MCP) is a standard for connecting AI assistants to third-party systems. These can be your databases, development environments, or popular software. The idea is that users (or businesses) can combine chatbots with the solutions they need.

MCP is an open-source standard developed by Anthropic (creator of the Claude). And while any company can use it, OpenAI and Google don't want to adopt a competitor's platform yet.

That's why many creators use MCP in combination with Claude.

MCP offers a massive advantage in terms of time and resources. Previously, you had to write code to connect an AI tool to an external system via an API. This meant that every connection had to be pre-coded. For example, if you had 1000 AI and 1000 external tools, you need 1M hard-coded connections via API.

But now it's simpler than that. Each AI can implement MCP once and then connect to thousands of external tools. The same thing works the other way around. The external tools have to create an MCP server just once, and all AI tools that support MCP can connect to them.

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The architecture is also straightforward: developers can either expose their data through MCP servers or build AI applications (MCP clients) that connect to these servers. Anthropic has three related components for developers:

• The Model Context Protocol specification and SDKs

• Local MCP server support in the Claude Desktop apps

• An open-source repository of MCP servers

These are all the tools you may need to implement your solution.

To make it even clearer, let's look at the cases.

I have already adopted several of them and strongly advise you to do so. We'll go from those useful to everyone to more specific usage scenarios.

And then, we'll look at how you can create your solution.