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Microsoft AutoGen
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Microsoft AutoGen

Active·★ 61.3k·MIT·Updated 2026-04-15
★ Most Popular★ Trending★ Essential

AutoGen is Microsoft Research's framework for building multi-agent AI applications in which agents can act autonomously or work alongside humans. Important: AutoGen is now in maintenance mode. It will not receive new features, it is community managed, and Microsoft recommends that new projects start with Microsoft Agent Framework, its enterprise-ready successor, using the official migration guide.

It remains relevant for teams with existing AutoGen code and for learning multi-agent patterns. Its layered design offers a Core API for event-driven, message-passing agents with local and distributed runtimes (including .NET and Python), an AgentChat API for common patterns such as two-agent chats and group chats, and an Extensions API for model clients, code execution and MCP tools. AutoGen Studio provides a no-code GUI for prototyping, and AutoGen Bench helps evaluate agents. Magentic-One, a multi-agent team for web and file tasks, is built on it.

Getting started: requires Python 3.10+. Install with `pip install -U "autogen-agentchat" "autogen-ext[openai]"`, and `pip install -U autogenstudio` for the GUI. Users upgrading from v0.2 should follow the migration guide, as the APIs changed significantly.

#Multi-Agent AI#AI Framework#Python#LLM Orchestration#No-code AI#Coding
$ Install
$ pip install -U "autogen-agentchat" "autogen-ext[openai]"
↗ Visit site★ GitHub
01

Features

01Framework for multi-agent AI applications
02Supports autonomous or human-collaborative agents
03Layered and extensible design (Core, AgentChat, Extensions APIs)
04No-code GUI for workflow prototyping (AutoGen Studio)
05Benchmarking suite for agent performance (AutoGen Bench)
02

Why choose it

+Well-designed layered architecture, from low-level event-driven runtimes to high-level chat patterns.
+Cross-language support (.NET and Python) and a distributed runtime option.
+Mature ecosystem of examples and research, including Magentic-One, AutoGen Studio and AutoGen Bench.
+MIT-licensed code, with a documented migration path to Microsoft Agent Framework.
03

Trade-offs

!In maintenance mode: no new features, community-managed support, and Microsoft points new users to Agent Framework instead.
!The v0.4+ APIs differ substantially from v0.2, so many older tutorials and code samples no longer apply.
!AutoGen Studio is explicitly not production-ready; deployed apps need their own authentication and security.
!Only connect trusted MCP servers, since they can run commands or expose data in your environment.
04

Compatibility

Python
Native
Verified via docs
.NET
Supported
Verified via docs
AutoGen Studio
Native
Verified via docs
OpenAI
Native
Verified via docs
Playwright MCP
Supported
Verified via docs
05

Quick start

1
$ pip install -U "autogen-agentchat" "autogen-ext[openai]"
06

Use cases

↳Developing multi-agent AI applications
↳Building specialized AI assistants (e.g., web browsing, domain experts)
↳Prototyping multi-agent workflows using a no-code GUI
07

How it compares

≈vs Microsoft Agent Framework: the official successor, with stable APIs and long-term support; choose it for new projects and keep AutoGen for existing code until you migrate.
≈vs CrewAI: CrewAI is actively developed and pairs role-based Crews with event-driven Flows for production automation; AutoGen offers lower-level conversation and runtime primitives.
≈vs MetaGPT: MetaGPT ships a fixed software-company workflow; AutoGen is a general toolkit for designing your own agent interactions.
08

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On this page
01Features02Why choose it03Trade-offs04Compatibility05Quick start06Use cases07How it compares08Alternatives
Stats
GitHub Stars★ 61.3k
Last commit5mo ago
StatusActive
LicenseMIT
CategoryMulti-Agent
Trend (30d)
+2.4k↑ 4.9%
Links
Documentation↗Discussion↗Issues↗Releases↗

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