What is in this article?

• What problem does MCP solve?

• AI Agents and Model Context Protocol (MCP)

• What Did We Do Before MCP?

• How Can AI Agents Leverage MCPs

• Setting Up Your MCP Server

• Integrating MCP Servers with APIs and External Ser …

What problem does MCP solve?

But First a Reminder: What is Model Context Protocol?

MCP is an open standard that creates a bridge between AI assistants (particularly Large Language Models) and the systems where data actually lives—including content repositories, business tools, development environments, and databases. Think of it as a "USB-C port for AI"—providing a universal connector that standardises how AI models receive information from and interact with external systems.

The protocol addresses a fundamental limitation of even advanced AI models: their isolation from real-time data and inability to interact with external systems in a standardised way. Before MCP, developers had to build custom integrations for each data source an AI model needed to access, creating a fragmented ecosystem of connectors.

Core Components of MCP

MCP architecture consists of two main elements: