Microsoft's open-source multi-agent conversation framework enabling LLM-powered agents to collaborate, write and execute code, and complete complex tasks through structured dialogue.
- Backed by Microsoft Research with strong academic foundations
- Code execution capability lets agents write and run Python automatically
- Flexible conversation patterns including group chats and hierarchical agents
- Deep integration with Azure OpenAI and the broader Azure AI ecosystem
- Steeper learning curve than CrewAI for basic multi-agent setups
- Code execution in sandboxes requires careful security configuration
- Documentation quality is inconsistent between v0.2 and v0.4 versions
| Free tier | ✓ Free tier |
| Pricing model | open_source |
| Features | |
| API | ✓ Available Docs ↗ |
| Pricing Plans | Open SourceFreeFull framework, self-hosted, MIT license Azure AI Foundry (hosted)Usage-basedRun AutoGen agents on Azure with managed infra |
| Platforms | |
| Integrations | Azure OpenAI, OpenAI API, Anthropic API, Google Gemini, Docker (for code execution), LangChain tools, GitHub |
| Homepage | https://microsoft.github.io/autogen/ |
AI Commentary
Microsoft AutoGen is distinguished by its research-backed approach to multi-agent systems, developed by Microsoft Research and deployed in production within Microsoft products. Its conversation-centric architecture allows agents to have structured multi-turn dialogues to collaborate on complex tasks, with built-in support for code generation and execution within sandboxed environments. This makes it particularly powerful for software engineering automation use cases. The framework is actively maintained and has seen a significant architectural redesign in v0.4, though this migration has caused documentation inconsistencies for developers upgrading from earlier versions.