Model Context Protocol (MCP)
The Model Context Protocol is an open standard for connecting AI applications to external tools, data, and prompts through a uniform interface.
The Model Context Protocol (MCP) is an open standard that specifies how AI applications exchange context with external systems. It defines a common client-server interface so that a model-powered application can discover and use tools, read data resources, and load prompt templates from any compliant server without custom integration code.
How It Works
In MCP, a host application embeds one or more clients, and each client connects to an MCP server. Servers expose three main primitives: tools, which are callable functions; resources, which are data the model can read; and prompts, which are reusable templates. The client and server negotiate capabilities over a defined message format, allowing the AI application to list what a server offers and invoke it in a consistent way. Servers can wrap databases, file systems, SaaS APIs, or internal services.
Why It Matters
Before standards like MCP, every connection between an AI application and an external system was a bespoke integration. A shared protocol reduces this duplication, makes tools reusable across different clients, and lets organizations expose their data and capabilities to AI safely and consistently. It is a foundational building block for agents and for grounding models in proprietary data.
Related Terms
MCP standardizes how an ai-agent and an large-language-model reach tools and data, complementing retrieval-augmented-generation and reusable prompt-engineering templates.