AutoGen — AI Agent Framework: Live Stats & TrendScore

AutoGen from Microsoft Research: we track how it’s faring against newer multi-agent frameworks, with weekly data on GitHub activity, community discussions, and production adoption signals.

GitHub data synced: Apr 15, 2026 • Sentiment updated: Apr 11, 2026

GitHub Statistics

Community Sentiment

Community Buzz: As one user on HackerNews said, 'I spent 20 minutes trying to log in to Teams on my phone today and I just couldn’t.', another user on Dev.to mentioned 'I built an AI editor for STRESS-CODING' showcasing the interest in AI-related topics

Pros & Cons

What People Love

AutoGen's flexibility, AI-powered tools on Dev.to

Common Complaints

Microsoft Authenticator issues, Complexity of AutoGen

Biggest Positive: AutoGen flexibility

Biggest Negative: Microsoft Authenticator issues

Why AutoGen Stands Out

AutoGen stands out from other agentic AI frameworks due to its unique approach to multi-agent orchestration, which enables the creation of complex workflows and automated tasks. By leveraging the power of OpenAI's GPT-4 model and Playwright's MCP server, AutoGen provides a robust and flexible platform for building a wide range of AI-powered applications. The framework's ability to support multiple agents and tools also makes it an ideal choice for developers looking to create comprehensive and specialized expert systems.

Built With

Build a research agent that reads academic papers and generates summaries — AutoGen's multi-agent orchestration enables this by chaining natural language processing and machine learning models, Build a web browsing assistant that automates tasks using Playwright MCP server — AutoGen's integration with MCP servers allows for seamless automation of web browsing tasks, Build a math expert assistant that solves complex equations — AutoGen's AgentTool and AssistantAgent enable the creation of specialized agents for specific tasks, Build a chemistry expert assistant that provides molecular weights and properties — AutoGen's support for multiple agents and tools enables the creation of a comprehensive chemistry expert system, Build a literature review generator that synthesizes information from multiple sources — AutoGen's multi-agent orchestration and natural language processing capabilities enable the automated generation of literature reviews

Getting Started

  1. Install AutoGen using the command `pip install -U 'autogen-agentchat' 'autogen-ext[openai]'`
  2. Create an account on OpenAI and export your API key as `export OPENAI_API_KEY='sk-...'`
  3. Install the AutoGen Studio using the command `pip install -U 'autogenstudio'`
  4. Configure your AutoGen environment by setting up the `autogen` directory and creating a `config.json` file
  5. Try running the `Hello World` example to verify that AutoGen is working correctly

About

A programming framework for agentic AI

Official site: https://microsoft.github.io/autogen/

Category & Tags

Category: development

Tags: agentic, agentic-agi, agents, ai, autogen, autogen-ecosystem, chatgpt, framework, llm-agent, llm-framework

Market Context

Competing with LangChain and CrewAI