AI Glossary
What it means, why it matters to your business, and where it shows up in a real build decision.
Also known as MCP
In plain terms
The Model Context Protocol is an open standard for connecting AI models to external tools and data sources through a consistent interface. MCP reduces the custom plumbing needed to give AI access to your systems, which lowers integration cost and avoids lock-in to one vendor's connectors.
Before MCP, connecting an AI to every new tool required custom wiring each time. MCP is the universal power socket: one standard interface and any compatible plug fits.
A company standardizes all internal AI integrations on MCP. Their engineering team adds a new data source in hours instead of weeks, because the interface contract is already defined and reused.
When building AI systems that need to connect to multiple internal or third-party tools, and you want to avoid rebuilding integrations for every new model or vendor.
For simple, single-tool integrations where the overhead of a protocol is not worth the standardization benefit. MCP pays off at scale and across multiple integrations.
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