Is MCP the Future of AI? Bull vs Bear Case

MCP: The Protocol That's Quietly Rewiring How AI Systems Connect

Jul 07, 2025

We're witnessing the second wave of AI. The first wave was AI wrappers—brilliant but isolated islands of intelligence. Companies like Perplexity, Cursor, and Replit built impressive tools that essentially put a beautiful interface on top of someone else's LLM. These AI wrappers were initially dismissed as "just an API call with a prompt", but they quietly became multi-billion dollar businesses.

Now we're entering something fundamentally different. The second wave isn't about building smarter models—it's about making AI systems talk to each other. Enter the Model Context Protocol (MCP), Anthropic's open standard positioning itself as the "USB-C of AI".

But is MCP truly the infrastructure that will connect our fragmented AI ecosystem, or just another overhyped protocol destined to become a footnote in tech history?

The Perfect Storm: Why Now?

Three massive trends are converging:

1. The Agentic Revolution is Real
Agentic AI—autonomous systems that can make decisions and perform tasks without human intervention—has moved from academic curiosity to business reality. Companies are deploying AI agents that can write code, manage workflows, and solve complex problems independently.

2. The Great AI Merger Wave
Grammarly's acquisition of Superhuman signals a new era of agentic office ecosystems. These aren't just feature additions—they're foundational shifts toward AI agents that collaborate across multiple tools.

3. The Infrastructure Gap
The biggest bottleneck isn't AI capability anymore—it's connectivity. How do you get your coding agent to talk to your email agent? This is where MCP becomes the critical infrastructure layer.

The Bull Case: MCP as AI's TCP/IP Moment

The Connectivity Revolution

Think about the early days of the internet. Computers existed, but they couldn't talk to each other. Then came TCP/IP—not flashy, but absolutely foundational. MCP is having its TCP/IP moment right now.

The numbers tell the story since its November 2024 release:

1,000+ MCP connectors built by the community in just months
Major Big Tech adoption: OpenAI, Google DeepMind, Microsoft, AWS, and Cloudflare all support MCP
Enterprise results: Companies like Block report 50-75% time savings on common tasks

From Islands to Ecosystems

The first wave created "isolated islands"—brilliant but disconnected tools. Your AI coding assistant couldn't access your CRM. Your customer service AI couldn't update your database. Each required custom integrations costing millions and taking months to build.

MCP changes this fundamentally. Instead of the M×N problem (connecting M AI models to N data sources requiring M×N integrations), MCP reduces this to M+N. One protocol, infinite possibilities.

Breaking Through the LLM Ceiling

There's growing evidence we may be approaching peak LLM capabilities. The future isn't about smarter individual models—it's about smarter systems of models working together. MCP enables this by allowing AI agents to access real-time information, perform concrete actions, and coordinate seamlessly.

The Network Effect is Accelerating

MCP adoption is showing classic network effect patterns. As one industry observer noted: "MCP has captured enough critical mass and momentum that it is already the presumptive winner of the 2023-2025 'agent open standard' wars".

The Bear Case: Just Another Overhyped Protocol?

Security Nightmare in Disguise

MCP essentially allows AI systems to execute code, access databases, and perform actions across your entire digital infrastructure. The security challenges are staggering:

Prompt injection attacks where malicious users trick AI into executing unauthorized commands
Tool permission escalation where combining tools leads to unintended data access
Authentication gaps in current implementations

Microsoft's security team warns that "MCP lacks built-in server protection and essential security measures required for enterprise-grade generative AI solutions".

The RAG Reality Check

Here's an uncomfortable truth: most of what MCP promises to do, RAG (Retrieval-Augmented Generation) already does—and does it more safely. RAG is:

More cost-effective than MCP's real-time tool calling
Easier to implement for most enterprise use cases
More secure by design, not requiring direct tool access

Protocol Fragmentation and Complexity

The current MCP landscape reveals troubling cracks:

Two incompatible specs (v1 from 2024 and v2 from 2025) with zero public clients supporting the newer version
Deployment nightmares with most MCP servers designed for single-tenant use
Too low-level for widespread adoption—where's the "HTTP layer" for MCP's "TCP/IP"?

Enterprise CTOs are cautious. As Rocket Companies' CTO notes: "We prefer to wait for more critical mass before embracing it in production".

The Complexity Trap

LLM reliability often negatively correlates with context and complexity. MCP, by design, increases both. Every new MCP server adds failure points, latency, and cognitive load on the LLM.

The Verdict: A Pivotal Moment

The bull case is compelling: unprecedented cross-industry adoption, real enterprise value creation, and the emergence of truly autonomous AI systems. MCP could indeed be AI's TCP/IP moment.

But the bear case is sobering: security challenges are massive, alternatives like RAG work well for most use cases, and enterprise adoption remains cautious.

Here's what I believe: MCP represents a fundamental bet on the future of AI. If you believe the future is agentic systems working together autonomously, then MCP is essential infrastructure. If you believe AI will remain primarily assistive tools with human oversight, then MCP is probably overkill.

The timing is perfect. Unlike previous "universal AI standard" attempts, MCP arrives when:

AI capabilities are mature enough to be truly useful
Multi-agent system complexity demands standardization
Enterprise adoption is accelerating rapidly

The ecosystem momentum is real. When you see major acquisitions like Grammarly-Superhuman specifically mentioning AI agent collaboration, this isn't just hype—it's infrastructure investment.

The alternative is chaos. Without MCP or something like it, we're heading toward a fragmented ecosystem of incompatible AI agents. The market will demand interoperability, and MCP is positioned to provide it.

The Bottom Line: Are You Ready for the Second Wave?

Whether MCP becomes invisible plumbing or the foundation of autonomous AI systems, one thing is certain: the second wave of AI is fundamentally different from the first. We're moving from isolated AI tools to collaborative AI ecosystems.

The companies, developers, and investors who understand this shift—and position themselves accordingly—will capture disproportionate value in the coming years.

The question isn't whether MCP will matter. The question is whether you'll recognize its importance before everyone else does.

What do you think? Are we witnessing the birth of the USB-C for AI, or just another overhyped protocol that will fade into obscurity? The next 18 months will tell us everything.