The role of MCP in context engineering
There’s no denying the excitement around Model Context Protocol (MCP), an open protocol for connecting AI assistants with external data, tools, and APIs. Since its debut by Anthropic in late 2024, thousands of MCP servers have emerged for devops, cloud, and beyond. Now that developers have integrated MCP servers into applications, and they have been battle-tested, usage patterns are emerging. For instance, supplying better context for AI is the most commonly cited primary value of using MCP, according to Zuplo’s State of MCP report released in early 2026. The Zuplo report also found that 63% of MCP users adopt MCP servers for accessing data sources such as documentation or knowledge bases. In software development, context engineering is the act of supplying AI coding agents with relevant data and capabilities to improve the accuracy and relevance of their outputs. It also involves optimizing the breadth of information to guide efficient processing. Such context can include coding style