This Week's Term: Model Context Protocol (MCP) - an open standard that enables AI assistants to connect with external data sources and tools through a universal interface, allowing applications to provide context to language models in a standardized way.
Think of MCP as a USB standard for AI. Before USB, every device needed its own proprietary connector - printers, keyboards, cameras all had different cables and ports. USB created a universal interface that any device could use. MCP does the same for AI applications: it creates a standardized way for AI models to connect with databases, APIs, file systems, and other tools.
Why this matters for business leaders: As organizations move from AI experiments to production systems, the integration challenge becomes critical. Without standards like MCP, every AI application requires custom connections to each data source and tool. With MCP, an AI assistant can plug into your CRM, your document repository, your analytics platform, and your custom internal tools through consistent interfaces.
The business implications are significant. MCP enables AI applications that were previously locked to specific platforms to become portable. An AI agent built with MCP connectors can theoretically work with any compatible data source, reducing vendor lock-in and enabling faster experimentation. For companies building AI-powered products, MCP support means easier integration with customers' existing systems - lowering adoption barriers and accelerating time to value.
The standard was introduced by Anthropic in late 2024 and has gained adoption across the AI ecosystem, with implementations now available for major development environments, databases, and enterprise tools. Companies like Block, Apollo, and Replit have adopted MCP for their AI integrations.
For leaders evaluating AI tools or building internal capabilities, MCP readiness is increasingly worth considering. Does the tool support MCP connectors? Can your internal AI applications expose their capabilities through MCP? These questions will become more important as the standard matures and becomes expected rather than exceptional.
To learn more about MCP and its technical implementation, Anthropic's documentation provides a comprehensive overview: modelcontextprotocol.io
For a clear, business-focused explanation of MCP and its strategic implications, I recommend this episode from Greg Isenberg's Startup Ideas Podcast. In about 20 minutes, Ross Mike breaks down MCP using the USB-C analogy and explains why - like HTTP and SMTP before it - standardized protocols tend to create significant business opportunities for those who understand them early.