What is Model Context Protocol?

MCP is like a librarian in a massive library. When an AI model requests information, the librarian knows exactly where to find the right book (application) and delivers it in a way the model can understand—ensuring smooth and efficient access to knowledge.

Overview

The Model Context Protocol (MCP) is an open protocol that standardizes how applications provide context to AI models. It creates a universal interface that allows AI models to securely interact with various local and remote resources through standardized server implementations.

Key Features
  • Provides a standardized protocol for connecting AI models to various data sources and tools
  • Enables secure interaction between AI models and both local and remote resources
  • Creates a universal interface that works across different AI models and applications
  • Simplifies integration of AI capabilities into existing tools and workflows
How It Works

MCP acts as a standardized interface layer between AI models and various resources. When an application implements the MCP server specification, it can provide context to any MCP-compatible AI model in a consistent way.

For example, when you connect a code editor to an AI assistant through MCP, the protocol ensures that the AI can securely access and understand the relevant code context, just like how plugging in a USB-C device ensures reliable data transfer regardless of the device type.

Getting Started

To start using MCP in your applications:

  1. Choose an MCP-compatible AI model for your application
  2. Implement the MCP server specification to provide context from your application
  3. Connect your application's MCP server to your chosen AI model
  4. Start using standardized AI interactions within your application