What’s MCP all about? Comparing MCP with LLM function calling

The Model Context Protocol (MCP) is gaining popularity as a method to enhance Large Language Models (LLMs) by integrating them with external tools, services, and data sources, creating a more scalable and reusable system than traditional LLM function calling. Unlike the function calling approach, where functions are defined and executed within each LLM application, MCP establishes standalone servers that expose functionalities to multiple LLM agents, allowing for a standardized interface that can be reused across applications. This approach is exemplified by the use of an MCP server to control smart home devices through Home Assistant, demonstrating how MCP can act as a bridge between AI applications and third-party services. MCP provides a higher level of abstraction by separating function definitions from LLM applications, enabling tool builders to create MCP servers that any MCP-compatible LLM can access, thus streamlining the integration process and avoiding the need for redundant implementations.

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