agent-framework vs adk-python
agent-framework: Microsoft Agent Framework is a comprehensive multi-language framework for building, orchestrating, and deploying AI agents. It supports both .NET and Python, offering features from simple chat agents to complex multi-agent workflows with graph-based orchestration.; adk-python: ADK (Agent Development Kit) is an open-source, code-first Python framework designed for building, evaluating, and deploying sophisticated AI agents with high flexibility and control. It simplifies the creation and orchestration of agent workflows, supporting everything from simple tasks to complex multi-agent systems, while being model and deployment agnostic.
Microsoft Agent Framework offers first-class .NET and Python packages with Azure/Foundry integration; Google ADK is Apache-2.0 and targets Google Cloud and Gemini workflows.
TL;DR
- You are starting a new Microsoft-ecosystem agent project in Python or .NET and want the official successor to AutoGen.
- You need built-in workflow checkpointing, middleware, OpenTelemetry tracing, declarative YAML agents, and a DevUI under MIT.
- You only need a small, single-file Python agent without a multi-package framework; Pydantic AI is lighter.
- You rely on Chinese LLM providers and realtime voice pipelines out of the box; AgentScope has dedicated support for those.
- You want Google's Apache-2.0, code-first toolkit with graph workflows, multi-agent hierarchies, a built-in dev UI, and evaluation tooling.
- Your team deploys on Google Cloud (Cloud Run or Vertex AI Agent Engine) or works across Python and ADK's other language editions.
- Your infrastructure is centred on Azure and .NET; Microsoft Agent Framework is tailored to that stack.
- You want a visual low-code workflow builder rather than writing Python code; n8n or Activepieces fit better.
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