Building a Python Workflow That AI Agents Can Discover Using APFlow

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A tutorial walks through building a small Python workflow that combines two regional request counts into one report using local sample data and SQLite. It explains how APFlow, an open-source orchestration engine, separates workflow structure from execution order, with independent regional tasks able to run concurrently. Python functions are registered as capabilities with schemas that can be exposed to agents through MCP, A2A, REST, and CLI adapters. The example runs without a model provider or API key and requires Python 3.11 or newer. The article also covers how dependency data flows between tasks, how capability contracts can be inspected, and how to move from a local example toward a production-style setup. APFlow is noted as still classified as Alpha, so the author recommends starting with verifiable outcomes before adding external integrations.

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