Alternatives to AutoGen
Microsoft framework for multi-agent conversations
AutoGen ranks #6 of 10 in AI agent frameworks, with an Alt Score of 86. It is licensed under MIT, free from Free and available on Linux, macOS and Windows. 13 of 13 checklist rows are verified against a public source.
AutoGen is an open-source Microsoft framework for building multi-agent applications with conversable, collaborating agents.
Python (and .NET) developers at teams comfortable building and running their own agent code, who want to prototype multi-agent LLM applications rather than use a managed platform.
An open-source, MIT-licensed multi-agent framework (AgentChat, Core, and Extensions APIs) plus AutoGen Studio, a local no-code UI for prototyping agent workflows; note that as of this writing AutoGen is in maintenance mode, with Microsoft directing new projects to Microsoft Agent Framework.
You compose agents backed by pluggable model clients (OpenAI, Azure OpenAI, local models, etc.), give them tools and memory, and coordinate them through built-in team patterns like round-robin/selector group chats or GraphFlow directed-graph workflows, with support for human-in-the-loop feedback, state persistence, and OpenTelemetry-based tracing.
Why people leave AutoGen
Dashed reasons are sourced facts; the rest are opinions. Vendors can dispute.
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Ranked alternatives
Ordered by Alt Score. Click any score to see the breakdown.
LangGraph is a low-level orchestration framework (by LangChain) for building stateful, multi-agent applications as graphs.
LlamaIndex is a data framework for building LLM applications and agent workflows over your own data (RAG + agents).
CrewAI is a Python framework for orchestrating role-playing, autonomous AI agents that collaborate as a crew.
Haystack (by deepset) is an open-source framework for building production LLM applications, RAG pipelines and agents.
Mastra is an open-source TypeScript framework for building AI agents, workflows and RAG, from the team behind Gatsby.
Agno (formerly Phidata) is a full-stack Python framework for building multi-agent systems with memory, knowledge and tools.
Semantic Kernel is a Microsoft open-source SDK for integrating LLMs and building AI agents in C#, Python and Java.
The OpenAI Agents SDK is a lightweight, provider-agnostic framework for building multi-agent workflows with handoffs and guardrails.
Pydantic AI is a Python agent framework that brings type-safe, structured outputs and dependency injection to LLM apps.
Feature comparison
Rows come from the AI agent frameworks checklist (17 rows). Human-verified cells only. ? means the value has not been verified.
| AI agent frameworks checklist | AutoGen | LangGraph | LlamaIndex | CrewAI | Haystack | Mastra |
|---|---|---|---|---|---|---|
| Pricing model | ||||||
| Starts at | ||||||
| License | ||||||
| Platforms | ||||||
| Open source | ||||||
| Language (Python) | ||||||
| Language (JS/TS) | ||||||
| Multi-agent orchestration | ||||||
| Graph / stateful workflows | ||||||
| Human-in-the-loop | ||||||
| Streaming support | ||||||
| Built-in memory / state persistence | ||||||
| Tool / function calling | ||||||
| Model-agnostic (multi-provider) | ||||||
| Observability / tracing integration | ||||||
| Managed / hosted deployment | ||||||
| RAG support |
Every fact and feature listed for AutoGen is verified against its own pages. Each alternative is sourced on its own page.
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License MIT verified 2026-07-16
Applies to code. Docs/content in the repo are separately licensed under CC-BY-4.0 per the same Legal Notices section and the LICENSE file.
grant you a license to any code in the repository under the MIT License
https://raw.githubusercontent.com/microsoft/autogen/main/README.md -
Pricing model Free verified 2026-07-16
AutoGen is a free, open-source library (MIT-licensed) with no paid tiers or first-party hosted offering.
Permission is hereby granted, free of charge, to any person obtaining a copy
https://raw.githubusercontent.com/microsoft/autogen/main/LICENSE-CODE -
Starts at Free verified 2026-07-16
Same basis as pricing_model: MIT-licensed OSS library, no cost to use.
Permission is hereby granted, free of charge, to any person obtaining a copy
https://raw.githubusercontent.com/microsoft/autogen/main/LICENSE-CODE -
Platforms Linux, macOS, Windows verified 2026-07-16
Installation docs give separate setup instructions for Linux/Mac and Windows.
Linux/Mac: python3 -m venv .venv source .venv/bin/activate Windows command-line:
https://microsoft.github.io/autogen/stable/user-guide/agentchat-user-guide/installation.html -
Status maintenance verified 2026-07-16
README also notes upgrading from v0.2 to the current stable (v0.4-based) architecture via a migration guide; Microsoft now directs new projects to Microsoft Agent Framework instead.
AutoGen is now in maintenance mode. It will not receive new features or enhancements and is community managed going forward.
https://raw.githubusercontent.com/microsoft/autogen/main/README.md -
Open source Yes verified 2026-07-16
grant you a license to any code in the repository under the MIT License
https://raw.githubusercontent.com/microsoft/autogen/main/README.md -
Language (Python) Yes verified 2026-07-16
AutoGen requires **Python 3.10 or later**.
https://raw.githubusercontent.com/microsoft/autogen/main/README.md -
Language (JS/TS) No verified 2026-07-16
README describes cross-language support for .NET and Python only; no official JS/TS SDK is mentioned anywhere in the README or docs.
It also support cross-language support for .NET and Python.
https://raw.githubusercontent.com/microsoft/autogen/main/README.md -
Multi-agent orchestration Yes verified 2026-07-16
You can use `AgentTool` to create a basic multi-agent orchestration setup.
https://raw.githubusercontent.com/microsoft/autogen/main/README.md -
Graph / stateful workflows Yes verified 2026-07-16
GraphFlow : A team that follows a DiGraph to control the execution flow between agents. Supports sequential, parallel, conditional, and looping behaviors.
https://microsoft.github.io/autogen/stable/user-guide/agentchat-user-guide/graph-flow.html -
Human-in-the-loop Yes verified 2026-07-16
The UserProxyAgent is a special built-in agent that acts as a proxy for a user to provide feedback to the team.
https://microsoft.github.io/autogen/stable/user-guide/agentchat-user-guide/tutorial/human-in-the-loop.html -
Streaming support Yes verified 2026-07-16
run_stream : Same as run() but returns an iterator of messages that subclass BaseAgentEvent or BaseChatMessage followed by a TaskResult as the last item.
https://microsoft.github.io/autogen/stable/user-guide/agentchat-user-guide/tutorial/agents.html -
Built-in memory / state persistence Yes verified 2026-07-16
it is useful to save the state of these components to disk and load them back later
https://microsoft.github.io/autogen/stable/user-guide/agentchat-user-guide/tutorial/state.html -
Tool / function calling Yes verified 2026-07-16
AssistantAgent is a built-in agent that uses a language model and has the ability to use tools.
https://microsoft.github.io/autogen/stable/user-guide/agentchat-user-guide/tutorial/agents.html -
Model-agnostic (multi-provider) Yes verified 2026-07-16
Since there are many different providers with different APIs, autogen-core implements a protocol for model clients and autogen-ext implements a set of model clients for popular model services.
https://microsoft.github.io/autogen/stable/user-guide/agentchat-user-guide/tutorial/models.html -
Observability / tracing integration Yes verified 2026-07-16
This capability is powered by the OpenTelemetry library, which means you can use any OpenTelemetry-compatible backend to collect and analyze traces.
https://microsoft.github.io/autogen/stable/user-guide/agentchat-user-guide/tracing.html -
Managed / hosted deployment No verified 2026-07-16
AutoGen Studio (the only first-party app-like tool) is run locally ("Run AutoGen Studio on http://localhost:8080") with no first-party hosted/managed offering.
It is **not meant to be a production-ready app**.
https://raw.githubusercontent.com/microsoft/autogen/main/README.md -
RAG support Yes verified 2026-07-16
The typically use case here is a RAG pattern where a query is used to retrieve relevant information from a database that is then added to the agent's context.
https://microsoft.github.io/autogen/stable/user-guide/agentchat-user-guide/memory.html
FAQ
Yes. Semantic Kernel, OpenAI Agents SDK and Pydantic AI have a free tier or are fully free. Free-tier limits in the comparison table are verified and dated.
LangGraph, LlamaIndex and CrewAI — every license claim links its source.