Sixteen thousand MCP servers in less than a year. That velocity didn't come from clever marketing—it came from architectural choices that removed every friction point from the developer experience.
Anthropic's Model Context Protocol made a specific bet in November 2024: optimize for developer autonomy over enterprise control. No approval processes to build a server. No vendor certification requirements. No centralized registry gatekeeping which implementations could exist. If you could write code, you could extend the ecosystem.
The design prioritized what developers needed to move fast. Developers could prototype an MCP server for their internal database in an afternoon. Claude 3.5 Sonnet could generate server implementations directly. Organizations testing agent workflows didn't wait for vendor roadmaps—they built what they needed.
At TinyFish, where we orchestrate web agents across dozens of external systems, we recognize why this mattered for web automation specifically. Integration complexity typically scales with the number of connections you need. Every new data source means another authentication flow, another API to learn, another maintenance burden. When you're coordinating agents across fragmented web surfaces—hotel booking systems, inventory platforms, pricing interfaces—that complexity compounds fast. MCP's standardization collapsed it. One protocol, many implementations.
Look at what happened when integration friction disappeared. Organizations report 25-40% efficiency gains in development cycles—that magnitude comes from eliminating the custom glue code that previously connected each new system. Microsoft integrated MCP across Copilot Studio and Azure AI Foundry. OpenAI adopted it for ChatGPT. Google followed. Developers built multi-agent systems coordinating across dozens of servers without writing integration layers from scratch.
The protocol's design assumed developers would handle their own security, authentication, and operational concerns. That assumption worked for rapid prototyping and ecosystem growth. Production deployment surfaced different challenges—ones the architecture left for organizations to solve themselves.