Let's Build a Trustworthy Model Context Protocol!

The Model Context Protocol (MCP) standardizes AI agent-tool interaction, accelerating agentic AI adoption through interoperability. This presents an opportunity to embed trustworthiness. As a standard and an interface between agents and tools, MCP becomes a natural enforcement point; any improvements to it automatically propagate to all systems using it. Analyzing MCP through EU Commission's Ethics guidelines for trustworthy AI, we identify three things: fundamental shifts in how trustworthiness works, critical challenges these shifts create, and strategic intervention points where protocol-level mechanisms can achieve ecosystem-wide impact. We argue how MCP's architecture provides a foundation for trustworthiness and propose practical improvements to strengthen it. This paper posits that building trustworthy MCP enables responsible agentic AI deployments.