The Rise of MCP and New Industry Trends

Standard protocols are gaining serious steam, new ways to code are emerging, and how we pay for AI is changing. It feels like the messy middle of building AI is finally starting to find some structure.

Look no further than the Model Context Protocol (MCP). This isn't just another spec document gathering dust; it's showing real traction where it counts – with developers. Its GitHub repository boasts over 40,000 stars, a number that handily outpaces the main home for the well-established OpenAPI Specification. That kind of developer interest signals a clear need for standard ways AI models talk to the outside world.

This developer energy isn't going unnoticed. The upcoming AI Engineer World's Fair in Summer 2025 is lining up its agenda around these exact themes. Expect dedicated sessions on MCP, alongside focus areas like "Local Lama" – a nod to the growing importance of running large language models closer to home – and the thorny, critical problem of teaching AI models "reasoning in RL."

Meanwhile, a concept dubbed "vibe coding" is bubbling up in developer circles. The idea here is making AI development more intuitive, letting people describe what they want using natural language instead of getting bogged down in syntax. It points to a future where building with AI might just be a lot more collaborative and accessible to folks without deep engineering chops.

The business side is also evolving. There's a noticeable pivot away from simply paying per token used toward outcome-based pricing for AI services. This signals a maturing market demanding tangible results. Companies want to pay for the value AI delivers – solving a customer issue, automating a task – not just the computational cost of running the model.

Efforts from major players like OpenAI with their Function Calling and Tool Calling specifications play into this broader trend. These features, enabling models to interact with external systems, are complementary pieces in the puzzle. They, like MCP, contribute to building a more standardized environment where diverse AI capabilities can be integrated and deployed effectively.

Now, while there's talk of major financial players like Jane Street and Bloomberg integrating MCP deeply, concrete, public confirmation of these specific adoptions in their core workflows remains somewhat elusive in recent announcements. While both firms are undeniably active in the AI space and invest heavily, the specifics on widespread MCP deployment are still in the realm of plausible, but unverified, claims for now.

These shifts, from developer standards to new coding paradigms and evolving economic models, highlight the dynamic nature of the AI engineering landscape. Staying informed on these fronts is how you remain Ahead of the Wave AI.