AutoGen — Microsoft's Framework for Multi-Agent AI Applications
About AutoGen
AutoGen is Microsoft Research's open-source framework for building multi-agent AI applications. It enables developers to compose conversational agents that collaborate, execute code, and use tools to solve complex tasks autonomously — powering everything from research assistants to automated software engineering workflows.
Key Capabilities
Microsoft Research-backed with active long-term development
Conversational multi-agent system with flexible agent topologies
Built-in code execution in sandboxed Docker environments
Human-in-the-loop support for supervised autonomous workflows
Works with any OpenAI-compatible API including Claude via proxy
AutoGen Studio provides a no-code UI for building agent teams
Standout Features
Multi-Agent Conversations
Compose agents that talk to each other to solve complex tasks
Code Execution
Agents write and run code in sandboxed Docker environments
Human-in-the-Loop
Pause for human review at any step in the autonomous workflow
Perfect for
Compare AutoGen
Community Buzz
Community Buzz
No recent posts yet
We are monitoring X for fresh discussions about AutoGen.
Similar Tools to AutoGen
Skills.sh
Open directory and leaderboard for reusable AI agent skills. Discover and install modular capabilities that enhance AI coding agents with procedural knowledge through simple one-command installation.
Claude Cookbook
Official collection of Jupyter notebooks and code recipes from Anthropic for building with the Claude API. Covers tool use, MCP integration, agent patterns, extended thinking, RAG, prompt caching, multimodal capabilities, and production patterns.
Langfuse
Open-source LLM observability and engineering platform for tracing, evaluating, and debugging AI applications. Langfuse provides production-grade monitoring with trace spans, cost tracking, prompt management, evaluation datasets, and a playground — all with no per-seat fees and a self-hostable MIT-licensed core.
Gemini Cookbook
Official collection of guides, quickstarts, and Jupyter notebooks from Google for building with the Gemini API. Covers multimodal prompting, function calling, grounding with Google Search, context caching, audio/video understanding, and agent patterns.
Semantic Kernel
Open-source SDK from Microsoft for integrating LLMs into applications using C#, Python, and Java. Semantic Kernel provides an agent framework, plugin architecture, prompt template engine, planner, and memory connectors — designed for enterprise AI orchestration with Azure OpenAI and other providers.
LangChain Hub
Community prompt and chain repository integrated with LangSmith. LangChain Hub lets developers discover, share, and version-control prompt templates, agent configurations, and chain definitions — a prompt registry that connects directly to the LangChain ecosystem for rapid AI prototyping.
Ready to try AutoGen?
Join thousands of developers who are already using AutoGen.















