I've been very happy with pydantic-ai, it blows the rest of the python ai ecosystem out of the water
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To check the workshop, I put together a demo repo: (I will add the slides too soon in my blog: https://www.petrostechchronicles.com/) https://github.com/Aherontas/Pycon_Greece_2025_Presentation_...
The idea was to show how multiple AI agents can collaborate using FastAPI + Pydantic-AI, with protocols like MCP (Model Context Protocol) and A2A (Agent-to-Agent) for safe communication and orchestration.
Features:
- Multiple agents running in containers
- MCP servers (Brave search, GitHub, filesystem, etc.) as tools
- A2A communication between services
- Minimal UI for experimentation for Tech Trend - repo analysis
I built this repo because most agent frameworks look great in isolated demos, but fall apart when you try to glue agents together into a real application. My goal was to help people experiment with these patterns and move closer to real-world use cases.
It’s not production-grade, but would love feedback, criticism, or war stories from anyone who’s tried building actual multi-agent systems. Big questions:
Do you think agent-to-agent protocols like MCP/A2A will stick?
Or will the future be mostly single powerful LLMs with plugin stacks?
Thanks — excited to hear what the HN crowd thinks!