Meet MCP: The "USB-C of AI Integrations"

Ever wish your AI agents could smoothly connect to any tool, file, or service—without custom hacks or endless glue code? That’s exactly what MCP does.

Vivek Rastogi

8/27/20251 min read

What is MCP?

MCP (Model Context Protocol) is like a translator and coordinator between AI models and tools.

  • It doesn’t create AI itself.

  • Instead, it helps AI talk to different apps, data sources, or APIs in an organized way.

Think of it as a universal “plug board” for AI:

  • You plug in your AI model on one side.

  • You plug in your apps (like Google Sheets, CRMs, databases, APIs) on the other.

  • MCP makes sure they understand each other.

Why do we use MCP?

Without MCP, connecting an AI model to real-world tools is messy:

  • You’d have to write custom code for every connection.

  • Each app has a different API (language), and AI can’t understand them automatically.

MCP solves this by providing a common format.

  • The AI says: “I need customer data.”

  • MCP fetches it from CRM in a way AI can understand.

Simple Example

Imagine you run a bakery and you want AI to manage orders:

  1. AI model → understands “Get today’s cake orders.”

  2. Your order system → has its own complicated way of giving data.

  3. MCP → stands in the middle and says:

    • “Hey Order System, give me today’s data.”

    • “Hey AI, here’s the data in a format you understand.”

The AI can then process it, analyze which cakes are selling best, and even trigger automated emails — without you coding every step.

Features of MCP
  • Standardized communication — all apps/tools use the same “language.”

  • Scalable — add new tools without rewriting everything.

  • Secure — handles authentication and data exchange safely.

  • Lightweight — doesn’t slow things down.

  • Flexible — works with any AI model (OpenAI, Anthropic, local LLMs).

Advantages of MCP
  • Faster integrations → no need to reinvent the wheel each time.

  • Reduced cost → fewer developers needed to wire up systems.

  • More reliable → fewer errors than custom scripts.

  • Future-proof → easily switch AI models without breaking connections.

How is it different from tools like n8n or Zapier?
  • n8n/Zapier → drag-and-drop automation for humans.

  • MCP → machine-to-machine protocol designed for AI models, not people.

  • In short, n8n helps you automate tasks, MCP helps AI automate tasks.