Microsoft AutoGen vs adk-python
Microsoft AutoGen: AutoGen is a versatile framework for developing multi-agent AI applications that can operate autonomously or in collaboration with humans. It offers a layered, extensible design, including Core and AgentChat APIs, along with developer tools like AutoGen Studio for no-code GUI development and AutoGen Bench for performance evaluation.; 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.
TL;DR
- You maintain an existing AutoGen v0.2 or v0.4 system, or want to run research artefacts built on it such as Magentic-One and AutoGen Bench.
- You want to reference its layered event-driven architecture while planning a migration to Microsoft Agent Framework.
- You are starting a brand-new project; Microsoft states AutoGen is in maintenance mode with no new features and recommends Microsoft Agent Framework.
- You expect AutoGen Studio to be a turnkey production web app (the README notes Studio is for prototyping only).
- 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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