Model Context Protocol (MCP)

Model Context Protocol (MCP) Overview

The Model Context Protocol (MCP) is an open standard released by Anthropic that enables connections between AI systems and external services. Think of MCP servers as "apps" for AI - they extend the functionality of AI systems in much the same way mobile apps extend the capabilities of smartphones. By providing a unified, standardized interface, MCP allows AI models to seamlessly access, interact with, and act upon information, eliminating the need for custom integrations for each data source.

This enables developers to build more powerful, context-aware AI applications that can securely leverage enterprise data, tools, and workflows. What makes MCP particularly powerful is its ability to chain multiple servers together, allowing AI systems to combine different capabilities to accomplish complex tasks.

MCP architecture diagram

Key Benefits

• Flexibility and Interoperability: MCP allows AI applications to easily switch between different services and tools without requiring major code changes.
• Security: MCP servers can be configured to control access to data and resources, ensuring that AI agents only have the necessary permissions.
• Abstraction: MCP hides the complexities of interacting with different services, making it easier for developers to build AI applications.
• Scalability: MCP servers can be deployed to handle large numbers of AI agents and requests.
• Ecosystem Integration: Multiple MCP servers can work together, allowing AI systems to combine capabilities for more complex tasks.

Learn more about MCP architecture and check out the implementation guide to start connecting to your own setup.