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AG2Open-source framework for building and orchestrating multi-agent LLM workflows.

4.7 (6)
Daniel NikulshynReviewed by Daniel Nikulshyn·Updated July 2026

Overview

AG2 is a developer framework designed to coordinate multiple LLM-powered agents that can collaborate, delegate tasks, and execute tools to solve complex problems. It provides abstractions for defining agent roles, conversation patterns, and shared memory, making it easier to build systems where several specialized agents work together rather than relying on a single monolithic prompt. The framework supports human-in-the-loop interactions, code execution, and integration with a range of model providers and external tools. It targets use cases such as research assistants, automated coding pipelines, data analysis workflows, and customer-facing agents that need structured reasoning and task decomposition. As an evolution of earlier multi-agent projects in the open-source ecosystem, AG2 emphasizes extensibility and community contribution, giving teams a foundation to prototype, optimize, and deploy agentic applications.

Key features

  • Multi-agent orchestration patterns
  • Configurable agent roles and conversations
  • Tool and function calling integration
  • Code execution support
  • Human-in-the-loop workflows
  • Provider-agnostic LLM connections

Pricing

Model
Free
Rating
4.7 / 5 (6)

Use cases

Multi-agent orchestration

Build, orchestrate, and evolve systems of AI agents to create a cohesive team with AG2.

Cross-platform coordination

Assemble dynamic teams of specialized personas across diverse platforms, such as AG2, Google ADK, OpenAI, and LangChain.

Unified state management

Maintain a shared brain across task lifecycles, ensuring enterprise-level collaboration and decision auditability.

Pros & Cons

Pros

  • Open-source and extensible
  • Strong support for multi-agent collaboration
  • Works with multiple LLM providers
  • Human-in-the-loop and tool-use built in

Cons

  • Requires developer expertise to set up
  • Multi-agent debugging can be complex
  • Documentation still maturing

Reviews

4.7

Average from 6 ratings.

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Yuki Mori

Yuki Mori

Mar 12, 2026

Years in this space

I've evaluated a lot of these over the years. What stands out here is configurable agent roles and conversations — handled better than most — and strong support for multi-agent collaboration. Requires developer expertise to set up is my one real gripe. Worth the time if this is your use case.

BC

Beatriz Costa

Jan 20, 2026

Years in this space

I've evaluated a lot of these over the years. What stands out here is code execution support — handled better than most — and open-source and extensible. Requires developer expertise to set up is my one real gripe. Worth the time if this is your use case.

Sofia Lindqvist

Sofia Lindqvist

Dec 6, 2025

Years in this space

I've evaluated a lot of these over the years. What stands out here is tool and function calling integration — handled better than most — and open-source and extensible. Worth the time if this is your use case.

Liam O’Connor

Liam O’Connor

Dec 6, 2025

Years in this space

I've evaluated a lot of these over the years. What stands out here is provider-agnostic LLM connections — handled better than most — and works with multiple LLM providers. Worth the time if this is your use case.

Jamal Carter

Jamal Carter

Sep 18, 2025

Use it every day

Honestly didn't expect to like it this much. Human-in-the-loop workflows is exactly what I needed, and open-source and extensible. I do wish requires developer expertise to set up, but I reach for it almost every day now and it just clicks.

Leila Hassan

Leila Hassan

Aug 12, 2025

Years in this space

I've evaluated a lot of these over the years. What stands out here is multi-agent orchestration patterns — handled better than most — and strong support for multi-agent collaboration. Requires developer expertise to set up is my one real gripe. Worth the time if this is your use case.

Q&A

What is AG2?

AG2 is an open-source Python framework for building, orchestrating, and scaling multi-agent AI systems. Built by the creators of AutoGen, AG2 enables developers and enterprises to compose systems of AI agents that collaborate to solve complex tasks.

Asked by Abebe Girma · Oct 23, 2025

What is a multi-agent AI framework?

A multi-agent AI framework provides the tools and abstractions to build systems where multiple AI agents work together. Instead of a single AI model handling everything, agents specialize in different tasks and coordinate with each other—leading to more reliable, scalable, and auditable AI workflows.

Asked by Tobias Hartmann · Sep 21, 2025

How is AG2 different from AutoGen?

AG2 is the production-ready evolution of AutoGen. While AutoGen is a research framework for multi-agent conversations, AG2 adds enterprise features like visual orchestration, persistent context, state management, and observability for deploying multi-agent systems at scale.

Asked by Carlos Mendoza · Sep 20, 2025

Is AG2 open source?

Yes. AG2 is open source at its core, available on GitHub under a permissive license. Enterprise features and managed hosting are available for teams that need production-grade support, security, and scalability.

Asked by Winifred Adeyemi · Aug 28, 2025

What programming languages does AG2 support?

AG2 is a Python-native framework. It integrates with popular Python AI/ML libraries and supports any LLM provider including OpenAI, Anthropic, Google, and open-source models. AG2 also supports agent communication protocols like A2A and MCP for interoperability.

Asked by Zain Malik · Aug 24, 2025

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