Anthropic’s Model Context Protocol (MCP) proposes a clean, stateless protocol for how large language models (LLMs) can discover and invoke external tools with consistent interfaces and minimal developer friction. This has the potential to transform isolated AI capabilities into composable, enterprise-ready workflows. In turn, it could make integrations standardized and simpler. MCP is not yet a formal industry standard. Despite its open nature and rising adoption, it is still maintained and guided by a single vendor, primarily designed around the Claude model family. A true standard requires more than just open access. There should be an independent governance group, representation from multiple stakeholders and a formal consortium to oversee its evolution, versioning and any dispute resolution. None of these elements are in place for MCP today. While MCP presents a promising direction, mission-critical systems demand predictability, stability and interoperability, which are best delivered by mature, community-driven standards. Protocols governed by a neutral body ensure long-term investment protection, safeguarding adopters from unilateral changes or strategic pivots by any single vendor. The idea behind MCP is that models should speak a consistent language to tools. Prima facie: This is not just a good idea, but a necessary one. It is a foundational layer for how future AI systems will coordinate, execute and reason in real-world workflows. The road to widespread adoption is neither guaranteed nor without risk.