Show HN: AI-powered web service combining FastAPI, Pydantic-AI, and MCP servers (opens in new tab)

Your views are not following a single convention: some of them return dictionaries, some return base JSONResponse objects, and others return properly defined Pydantic schemas. I didn't run the code, but I'd venture to guess your generated documentation is not comprehensive, nor is it cohesive.

I'd also further extend this into your agent services; passing bare dictionaries with arbitrary fields into what is supposed to be a modular logic handler is pretty outdated. You're defining a functional (methods) interface; data structures are the other half of the equation.

This plays into the way that Agents (as in the context of this system, versus Pydantic AI agents) are wrapped arbitrarily. I'd favor making the conversion from a Pydantic agent to a native agent part of the system's interface design, rather than re-implementing a subset of the agentic functions in your own BaseAgent and ending up with an `agent.agent` context.

Also, since this is a web-centric application (that leverages agents) dropping all of your view functions into main.py leaves something to be desired; break up your views into logical modules based on role.

Everyone's learning, and I hope this helps someone in their journey. Kudos for putting your code out there as a resource; some of us can't help ourselves from reading it.

Would be great if you can add the slides or video of the presentation to the repo. Maybe also add a description and update the summary at the top?

It seems like the project is a multi-agent playground & demo to learn how to make AI agents work together?