What Is the Model Context Protocol (MCP)?
A standardized way for AI applications to connect to external tools and data sources — meant to replace one-off custom integrations with a common, reusable interface.
A common interface instead of one-off integrations
The Model Context Protocol (MCP) defines a standard way for an AI application to discover and call external tools and data sources, so a tool built to speak MCP can be plugged into any MCP-compatible AI application, instead of every integration needing custom, one-off code for each specific pairing.
The problem it addresses
Without a shared standard, connecting an AI assistant to N different tools traditionally meant building roughly N different custom integrations, and each new AI application wanting to use those same tools meant repeating that work again. A common protocol turns that into a "build once, connect to many" problem instead.
How it relates to function calling
MCP builds on the same underlying idea as function calling — a model requesting a structured action with arguments — but standardizes how tools describe themselves and how that connection gets established, rather than leaving that format up to each individual integration.
Frequently Asked Questions
What is the Model Context Protocol?
A standardized protocol for connecting AI applications to external tools and data sources, so integrations can be built once and reused across any compatible AI application rather than custom-built for each pairing.
Why does a standard protocol for AI tools matter?
Without one, connecting an assistant to many tools means building many one-off custom integrations. A shared standard lets a tool builder support many AI applications, and an AI application support many tools, without duplicated integration work.