The Model Context Protocol (MCP) is an open standard that lets AI applications connect to external capabilities — databases, APIs, file systems, developer tools — through a uniform interface, rather than every integration being bespoke. An MCP server exposes tools and resources; an MCP-capable client (like a coding agent) can discover and call them.
For AI-assisted engineering, MCP matters because it gives models grounded, real-time access to the systems an engineer actually works in: the repository, the issue tracker, the deployment platform. That context is what separates a model guessing from a model reasoning over your actual environment.
Standardizing the connection also makes the ecosystem composable — a tool built once works across any MCP-compatible assistant — which is why it has become a common backbone for agentic developer workflows.