The AI breakthrough developers can't stop talking about: MCP

What if AI tools could work with live data ... without painful custom integrations?

Right now, most AI applications are stuck in the past. They're smart, but disconnected—relying on outdated training data or requiring fragile, one-off API connections. If you've ever hacked together a function-calling system, struggled with vendor-specific integration quirks, or wasted time hardcoding API connectors for every AI tool you use, then you already know the problem.

Enter Model Context Protocol (MCP).

Instead of forcing developers to reinvent the wheel for every AI integration, MCP introduces a standardized, open-source way for AI applications to fetch real-time data, interact with external systems, and execute actions—without endless custom coding.

In today's newsletter, I'm breaking down:

• What MCP actually does (and why it matters)

• How MCP compares to traditional AI integrations

• How to start experimenting with MCP today

Let's go.

What is MCP, exactly?

Imagine buying the most advanced smartphone ever—but there's a catch: it doesn’t connect to Wi-Fi, Bluetooth, or your cellular network. Weird, right?

The phone has amazing potential, but it can only use the apps and data already stored inside. No software updates, no live sports scores, no way to pull in new information. Frustrating.

Believe it or not, this is how most AI applications worked until recently.

AI apps like Claude are incredibly smart—but stuck in the past. Traditionally, they could only rely on the information they were trained on, just like that disconnected phone.

That's where MCP changes things.

In late 2024, AI researchers at Anthropic decided enough was enough. They realized developers were constantly reinventing the same wheel—building custom pipes to connect AI apps to external systems. Each integration was fragile, repetitive, and inefficient.

Anthropic had a big idea: “What if there was one simple, universal way for AI applications to access external data?”

Thus, the Model Context Protocol (MCP) was born—an open standard released publicly as open-source in November 2024.

MCP is an open standard that allows AI applications to seamlessly fetch and use real-time external data—without the hassle of building custom integrations for every use case.

We can also think of it as a universal connector—like a USB-C port or Wi-Fi—for AI apps. Instead of endless custom coding, developers now only need to integrate each external data source once as an MCP Server, and every MCP-compatible AI app can use that integration seamlessly.

MCP has been widely embraced as transformative for AI development. However, with its rapid adoption, the community has also raised important concerns—especially around security and data privacy.

MCP’s concept may seem intuitive, but let’s peek under the hood—it’s cleverly engineered, just like a modern car designed for safety, efficiency, and ease of use.

• Security: Think of MCP’s security like giving a guest limited access to your home—you don’t hand them your primary keys, just the keys to the rooms they need. MCP similarly ensures AI apps only access precisely what they need, reducing the risk of accidentally exposing sensitive information. But just as you’d install security cameras around your home, experts recommend closely monitoring and classifying data to protect it from misuse or unwanted access.

• Performance and scalability: Imagine inviting friends to dinner. Traditional APIs are like cooking a completely separate meal from scratch for every guest—time-consuming and exhausting. MCP, however, is like a potluck dinner—each guest brings their own dish, making it easy to add more people without extra effort. Thanks to lightweight JSON-RPC communication, MCP seamlessly supports multiple integrations without slowing down.

Before MCP, integrating AI with external data meant reinventing the wheel for every application—slow, tedious, and inefficient. MCP changed the game entirely, integrating external data is like assembling ready-made furniture with clear instructions. A growing collection of open-source MCP connectors means you spend less time coding integrations and more time creating amazing AI experiences.

How does MCP work?

Now that we know what MCP is, let’s explore how it works behind the scenes to make AI applications fully connected: