Tools/microsoft/autogen

AutoGen

Programming framework for agentic AI

59.8k+142/wkestablishedPythonCreative Commons Attribution 4.0 Internationaltrending

The Lens

By Erik Loyd, SaaS CEO and former COO/CFO of an AWS Premier Partner.

Updated Jun 2026

AutoGen is Microsoft's framework for building multi-agent AI systems, where several agents with different roles, tools, and instructions work together or alongside a human to finish a task. You define the agents, and AutoGen manages how they talk, call tools, run code in a sandbox, and pause for your approval. It handles the plumbing of multi-agent coordination so you are not hand-rolling conversation state and tool routing.

Here is what you need to know before building on it: AutoGen is now in maintenance mode. Microsoft has named a successor, the Microsoft Agent Framework, and is steering new users there. AutoGen still works, the v0.7 line is stable, and the community manages it going forward, but it will not get new features. The code is MIT (docs and examples are CC-BY-4.0), so it stays free and forkable.

If you already run AutoGen in production, you are fine for now, but plan a migration path to the Microsoft Agent Framework rather than starting new work here. If you are picking a multi-agent framework today, start with the successor, or look at CrewAI and LangGraph, which many find easier for simpler workflows. Solo and small teams experimenting: it is still useful for learning the patterns, just know you are learning a frozen API.

The catch is that one, stated plainly: this is a framework Microsoft has stopped developing. The star count and the pile of existing tutorials make it look like the safe default, but maintenance mode means no fixes for new model behaviors and no new capabilities. Building something long-lived on a frozen framework is a decision, not a default.

Free vs Self-Hosted vs Paid

fully free

Fully open source. The framework code is MIT, documentation/examples are CC-BY-4.0. No paid tier from Microsoft for AutoGen itself.

Your costs are LLM API calls:

  • OpenAI GPT-4o: ~$2.50/1M input tokens, $10/1M output
  • Azure OpenAI: similar pricing
  • Local models via Ollama: free but slower

Multi-agent systems multiply your API costs because agents converse with each other. A 4-agent workflow processing one task might use 5-10x the tokens of a single-agent approach. Budget accordingly.

Autogen Studio (the visual UI) is also free and included.

Free framework. Your cost is LLM API usage, which multi-agent patterns multiply significantly.

Self-hosting ops:moderate

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74/100 · B+
Adoption30/30
Maintenance10/25
Community9/20
License15/15
Analysis10/10

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