By Dan Jaye, CEO

Looking across the landscape I’ve mapped in this series – from architectural transformation to simulation-driven development to industry-specific standards – one conclusion becomes inescapable: MCP will be as foundational to AI as OpenAPI is to web development today. And it’s happening faster than anyone predicted.

The numbers tell a compelling story: from Anthropic’s November 2024 announcement to over 5,000 active MCP servers by May 2025. OpenAI officially adopted MCP in March 2025, and Google DeepMind confirmed support in upcoming Gemini models. This isn’t gradual adoption – it’s an industry-wide recognition of architectural necessity that technology analysts are calling unprecedented.

The Registry Wars are Beginning

I predict we’ll witness an explosion of MCP registries – repositories where developers discover, validate, and deploy AI components. But the competition won’t center solely on technical compatibility. The battleground will be trust, compliance, and reputation management.

Think Apple App Store meets enterprise software governance. Organizations will need to evaluate not just whether a component works, but whether it meets security standards, compliance requirements, and performance benchmarks.

Model context protocol comes in handy when real-time, rich, and personalized context is needed for LLMs or AI agents, especially in regulated or high-trust environments. The registries that solve trust and governance will dominate.

Enterprise Adoption Will Accelerate

I’m already seeing large enterprises mandate MCP compatibility in vendor evaluations. Just as OpenAPI became table stakes for SaaS procurement, MCP compatibility will become the default requirement for enterprise AI integrations.

Enterprise adoption is accelerating, with businesses standardizing on MCP for secure, scalable AI implementations. Spring AI MCP and Azure OpenAI MCP are gaining traction for robust, enterprise-grade solutions.

The AI Component Marketplace Transformation

Here’s the transformation that excites me most: AI component marketplaces. Imagine browsing sentiment analysis engines like mobile apps. A/B testing new targeting algorithms on demand. Purchasing and deploying optimization components without rewriting your technical stack.

The diversity of MCP implementations – from enterprise giants like Spring AI MCP to creative innovators like Figma MCP – reflects the protocol’s versatility. As AI adoption skyrockets, these MCPs are reducing integration friction, cutting costs, and enabling AI to deliver hyper-relevant results across industries.

Your Strategic Moves Start Soon

Based on everything I’ve outlined – from orchestration concepts to architectural patterns to simulation methodologies – the time for strategic positioning is now:

Define Your Role: Will you be a standard setter (like MCMAP for marketing)? A platform provider (registries, tools, governance)? Or a specialist (vertical-focused, domain-expert components)?

Build MCP-Native Capabilities: Develop solutions that demonstrate immediate value within the MCP ecosystem rather than attempting to retrofit existing architectures.

Engage in Trust Frameworks: Participate in the governance and certification frameworks before others establish the rules you’ll be forced to follow.

The Window is Open, But Not Forever

But companies that hesitate will find themselves implementing other organizations’ standards, integrating with other companies’ platforms, and competing in markets others have defined.

MCP represents the infrastructure layer. But what we construct on top of it – the applications, the marketplaces, the standards, the governance frameworks – that’s where the enduring value will be created.

The future belongs to those who help architect it.