ToolProduction Ready

autogen

Name: autogen
Rating: 5.0 (54502 reviews)
Author: microsoft

by microsoft

Python framework for building and orchestrating agentic AI workflows

Python

Updated Jan 22, 2026

54.5k

Stars

8.2k

Forks

View on GitHub

Overview

Enables building and orchestrating agentic AI applications with composable agents and message-passing workflows. Provides a Python framework for defining agents, roles, tool connectors, and multi-agent conversation patterns so teams can prototype complex delegations and pipelines. Includes support for synchronous and asynchronous flows, planner/actor setups, and integrations with major LLM providers. Hierarchical Multi-Agent Pattern and Agent Protocol.

Why It Matters

As agents delegate tasks and collaborate, instrumenting interaction patterns and failure modes becomes essential for trust. Autogen gives practitioners a reusable platform to construct realistic multi-agent workflows that surface delegation behavior, error propagation, and decision boundaries. That makes it easier to run pre-production evaluations and capture the signals needed for agent-to-agent evaluation and reputation systems. Leveraging the Model Context Protocol (MCP) Pattern can help standardize these interactions.

Best For

Teams prototyping or producing multi-agent systems that need structured agent roles, delegation patterns, and integrations with major LLMs. For interoperability, consider adopting the A2A Protocol to enable smooth agent-to-agent communications.

How It's Used

Composing specialist agents that delegate subtasks and aggregate results
Prototyping agent pipelines to reproduce and debug multi-agent failure modes
Injecting evaluation hooks to measure agent track record and behavior during runs

Avoid common pitfalls

Learn what failures to watch for