Model Context Protocol (MCP)
An open standard for connecting AI assistants to external data sources, tools, and services through a unified interface.
Definition
Model Context Protocol (MCP) is an open specification that standardizes how AI models connect to and interact with external systems. It provides a universal way for AI assistants to access databases, APIs, file systems, and other tools without custom integrations for each data source.
MCP acts as a bridge between AI models and the real world, enabling them to read files, query databases, execute code, and interact with services through a consistent protocol that any AI provider can implement.
Why It Matters
MCP simplifies AI integration for businesses by eliminating the need to build custom connectors for every tool and data source. Teams can connect their AI assistants to CRMs, analytics platforms, and internal databases through standardized MCP servers.
This interoperability means organizations aren't locked into specific AI vendors—they can switch models while keeping their integrations intact.
Examples in Practice
A marketing team connects their AI assistant to their analytics platform via MCP, allowing the AI to directly query campaign performance data and generate real-time insights.
An agency builds one MCP server for their project management tool, instantly giving all their AI assistants access to client briefs, timelines, and deliverables.
A content creator uses MCP to connect their AI writing assistant to their CMS, enabling the AI to directly publish, schedule, and manage content.