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anmolmalviya05

Model Context Protocol (MCP) Explained - In Simple Terms for Data Professionals

The Evolution of AI Applications

Let’s zoom out for a moment.

Phase 1: Pure LLMs

We started with large language models (LLMs) like ChatGPT. They could:

  • Summarize
  • Generate text
  • Explain concepts
  • Write code

But they were limited to their training data. They couldn’t fetch live stock prices. They couldn’t query your private database.

 

Phase 2: Agentic Systems

Then we started building agent-based applications. Now LLMs could:

  • Call APIs (like Yahoo Finance)
  • Search the web
  • Query databases
  • Read PDFs
  • Execute workflows

But to make this happen, developers had to write a lot of glue code.

 

What Is Glue Code? (The Hidden Pain)

 

Imagine you’re building an AI app that generates a stock comparison report between NVIDIA and Tesla.

The app needs to:

  • Pull company descriptions (LLM can do this)
  • Fetch latest stock price (API call)
  • Retrieve financial metrics (Database/API)
  • Get recent news (Web search)
  • Summarize everything
  • Your AI engineer builds:
  • LLM at the center
  • Yahoo Finance API integration
  • Web search integration
  • Private database integration
  • Custom prompts
  • Error handling
  • API schema parsing

All connected through custom Python or TypeScript code.

That integration layer? That’s glue code.

Now imagine:

20 such AI apps in one company, Millions across the world

That’s a maintenance nightmare.

If Yahoo changes their API? You update code everywhere.

 

The USB-C Moment for AI

Think about old computers. You had:

 

VGA cable, HDMI, Separate charging port, Separate USB, Separate audio jack, 

Today?

Everything connects through USB-C. One standard interface.

 

MCP is the USB-C for AI applications.

Model Context Protocol (MCP) is a standardized way for LLMs to interact with:

  • Tools (APIs)
  • Resources (files, databases)
  • Prompts

Instead of every developer writing custom integration logic, MCP defines:

  • A common structure
  • A common communication protocol
  • A common schema

Now tools expose themselves through MCP servers, and AI apps connect to them via an MCP client.

Let’s Relate This to Data Professionals

If you're a Power BI Developer, think of this like:

  • Before: Everyone builds custom connectors
  • Now: Use certified connectors with standard interface

If you're a Data Engineer, think of this like:

  • Before: Custom REST integration everywhere
  • Now: Standardized data contract

If you're a Data Analyst, think of this like:

  • Before: Everyone calculates KPIs differently
  • Now: Central semantic model

MCP is bringing semantic standardization to AI-tool interactions.

 

Why This Is Powerful

Without MCP:

  • Every team writes integration code
  • Maintenance burden increases
  • API changes break systems
  • Duplicate effort everywhere

With MCP:

  • Tool provider builds the MCP server
  • Developers consume standardized interface
  • Centralized maintenance
  • Reduced glue code

This is very similar to how:

  • You consume Power BI REST APIs
  • You use Azure SDKs
  • You rely on standard SQL interfaces

Important: MCP Does NOT Replace REST

It wraps it.

Internally:

  • HTTP calls still happen
  • APIs still exist
  • Authentication still exists

MCP standardizes the AI interaction layer.

Why Power BI Developers Should Care

Think ahead:

  • AI-powered semantic layer interaction
  • AI interacting with Fabric items
  • AI auto-generating reports from business language

MCP could become the standard layer between:

LLMs ↔ Enterprise Data Systems

Reality Check

There is hype. Yes.

But we are early. MCP has potential.

But:

  • Adoption is still growing
  • Ecosystem maturity is developing
  • Governance patterns are evolving

Just like:

  • Early days of Azure
  • Early days of Power BI
  • Early days of Lakehouse

Final Thoughts

If you're in data: You don’t need to build MCP servers tomorrow.

But you should understand the direction.

The future stack may look like:

Lakehouse → Semantic Model → MCP Server → AI Agent → Business User

MCP might become the standard bridge between enterprise data and AI.

 

Join Power BI Corner Group: https://chat.whatsapp.com/KqsU8HUXcsaIoUEyq0zCIq


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Comments

Nice blog 👌 

Very well explained. I like the analogy of MCP with C type USB. It really helped to imagine the concept and make it stick.

Thanks,

Regards -Amit Devkatte

Thank you @AmitDevkatte , @AhmedMamdoh