A common problem in production happens when an agent can see many tools, but it still needs to know which action is appropriate now, what must happen first, and when it should stop and ask. The non-deterministic nature of AI agents makes this particularly challenging without structured guidance.
The HAPI Capability Graph and Capability Planning address this problem by providing structured guidance for the agent.
Every team adopting MCP eventually hits the same fork in the road: reimplement your business capabilities as an MCP server, or expose what you already have through one.
The first path feels faster on day one. It's also how a second, hidden application — a shadow of the one you already trust — gets built without anyone deciding to build it.
AI has dramatically reduced the cost of writing code. It has not reduced the cost of owning it.
That distinction may become one of the most important architecture lessons of the AI era.
Today, almost anyone inside an engineering organization can open an AI coding assistant and say:
"Here is my API. Build an MCP server for it."
If your tool server needs to interrupt the model to ask a question, ask why the question wasn't answerable before the call started.
MCP elicitation is a real, spec-defined capability, and it solves a real problem. It's also becoming a convenient place to hide a design problem instead of fixing it.
The expensive part of enterprise AI is often not the model. It is rebuilding what already works.
Many software companies have spent years, and sometimes decades, turning business rules, customer needs, operational lessons, security controls, and hard-won reliability into production APIs.
Then AI arrives, and the first instinct is often: We need to rebuild the platform for agents.
Your API is already production-hardened. It has authentication, validation, rate limits, monitoring, and a battle-tested OpenAPI spec describing every operation. None of that changes when an AI agent becomes the caller instead of a browser or a mobile app.
The most valuable MCP server may be the one that refuses to become your application.
MCP is moving toward a clearer architectural truth: servers should be stateless.
Every line of business logic you duplicate into an MCP creates another place where your system can eventually disagree with itself.
And that disagreement has a cost.
Every few months, our industry declares the next abstraction layer "the new HTTP."
First it was SOAP.
Then REST. Then GraphQL. Then gRPC.
Now, it's MCP.
Today, we crossed a major milestone.
👉 The HAPI MCP Registry is now available in the ChatGPT marketplace, officially aligning with the ecosystem driven by OpenAI.
And this is bigger than a feature release.
This is a shift in how APIs and AI finally connect.
