I am talking to a number of folks about documenting their MCP servers. Others about discovering them. Others about governing them. Generally, we are mostly talking about being able to just see the MCP wave of API expansion that has occurred across your average enterprises. This expansion phase isn’t much different than previous waves of REST, GraphQL, gRPC, Websockets, and Kafka expansions–it just happened faster and wider that most of those.
I published a prototype API docs that generates documentation for API, MCP, and Agent Skills side by side last week. I called the POC, “See”. I am a big fan of “seeing APIs” and “seeing integrations”. I’ve been doing about an hour of research a week into what is happening when it comes to MCP documentation, discovery, and other goings on with MCP at the core and the edges. There isn’t a lot of service or tooling for the seeing of MCP that is required for governance of APIs, and general attitudes seem to be that AI will do the seeing for us.
While I am not convinced that what has helped us find and see APIs historically will translate into helping us see the next generation of APIs, but I am also not convinced that AI will help us discover and see all of our APIs, and the skills, SDKs, and clients needed to engage with those APIs. I want to clarify here–MCP is an API. I see Microsoft, Google, and others going all in on their developer education being delivered via MCP, and I suspect more of the resources that occurs within developers will be shifted to be available via MCP, with as much of the activity as we can will be driven by skills.
I don’t think we will be able see what we need to see in an API-powered chat interface. And since agent’s don’t see, I know they won’t be able to see everything we need. They will help see a lot of what exists in the cracks and shadows that we couldn’t see historically with APIs, but there will be entirely new blind spots to wrestle with. I am finding some really interesting ways of seeing APIs and their properties at scale using machine-readable artifacts, which is enabled using Claude, ChatGPT, and Gemini. I will keep pushing forward automation to help discover and document APIs, as well as visualizations that help us see all of that. I am most interested in doing it in ephemeral and evolving ways, rather than the static or even dynamic ways we’ve done historically.
Seeing APIs is a massively unsolved problems. We just expanded that problem 1000x with AI and MCP. Just as we were beginning to get a hadle on the governance of HTTP APIs, we’ve expanded our API sprawl using GraphQL, Kafka, gRPC, and now MCP. There is so much more to see. There is so much more work to be done. With most people’s strategy that AI will sort it out for us. I hope y’all are right.
