Show HN: Auto-Match – How We Built Receipt-to-Transaction Matching (Open Source)
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Show HN: AI-powered web service combining FastAPI, Pydantic-AI, and MCP servers
Show HN: AI-powered web service combining FastAPI, Pydantic-AI, and MCP servers Hey all! I recently gave a workshop talk at PyCon Greece 2025 about building production-ready agent systems.<p>To check the workshop, I put together a demo repo: (I will add the slides too soon in my blog: <a href="https://www.petrostechchronicles.com/" rel="nofollow">https://www.petrostechchronicles.com/</a>) <a href="https://github.com/Aherontas/Pycon_Greece_2025_Presentation_Agents" rel="nofollow">https://github.com/Aherontas/Pycon_Greece_2025_Presentation_...</a><p>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.<p>Features:<p>- Multiple agents running in containers<p>- MCP servers (Brave search, GitHub, filesystem, etc.) as tools<p>- A2A communication between services<p>- Minimal UI for experimentation for Tech Trend - repo analysis<p>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.<p>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:<p>Do you think agent-to-agent protocols like MCP/A2A will stick?<p>Or will the future be mostly single powerful LLMs with plugin stacks?<p>Thanks — excited to hear what the HN crowd thinks!
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