Model Context Protocol (MCP)

Model Context Protocol (MCP) is an open standard introduced by Anthropic in November 2024 that defines how large language models communicate with external tools, data sources, and services in a uniform way. It replaces the fragmented N×M bespoke integration problem with a single client-server protocol built on JSON-RPC, exposing three core primitives: tools (callable functions), resources (data the model can read), and prompts (reusable templates). MCP has since been adopted by OpenAI, Google DeepMind, and dozens of developer platforms, making it a de-facto lingua franca for agentic AI systems.

As companies move from single-turn LLM calls to autonomous agent pipelines, they need a standard way to let those agents access databases, APIs, file systems, and other services—and MCP fills that role. Hiring for agentic AI roles in 2026 increasingly lists MCP literacy alongside tool-calling and RAG, because it directly determines how quickly a team can wire a new model into existing enterprise infrastructure. Engineers who can build and secure MCP servers unlock faster iteration cycles and interoperability across the growing MCP server ecosystem of thousands of published connectors.