Model Context Protocol (MCP) is an open-source standard that enables communication between AI agents and external data sources. Unlike APIs, which are designed for developers, MCP serves AI assistants and provides a way to interact with external systems. The protocol defines how agents can elicit user input, enable automated agents, and perform complex tasks.
At its core, MCP utilizes the client-server model, with three main features: tools, resources, and prompts for servers, and elicitation, roots, and sampling for clients. Instead of explicitly calling APIs, agents select and use the appropriate tools based on user input, allowing for a more responsive workflow between LLMs and users.
The need for MCP arises from the shift in user interaction from developers to AI agents. APIs are deterministic, while AI agents make autonomous decisions using probabilistic LLMs. MCP solves this problem by providing high-level abstraction that wraps functionality rather than API endpoints. This enables LLM models to perform tasks like searching or booking without relying on repeatable results.
MCP has seen a steady rise in popularity since its release in 2024, with over 6,400 registered servers and adoption from major players like OpenAI and Google. As the protocol continues to mature, it’s expected to transform what AI systems can accomplish in their second year of widespread adoption.
Source: https://thenextweb.com/news/rise-of-model-context-protocol-in-the-agentic-era