multi-agent AI agent framework
AG2 is a Python framework for building and orchestrating multi-agent AI systems with LLM integration, tool use, and human-in-the-loop workflows.
Same problem, same approach. Swapping one for another is a config change, not a rewrite.
Choose when you want a Google-backed Python agent toolkit with built-in evaluation and deployment paths.
An open-source, code-first Python toolkit for building, evaluating, and deploying sophisticated AI agents with flexibility and control.
Choose when you want a lightweight Python multi-agent workflow library tightly integrated with OpenAI APIs.
A lightweight, powerful framework for multi-agent workflows
Choose when you want a Microsoft-backed Python/.NET framework for orchestrating multi-agent workflows.
A framework for building, orchestrating and deploying AI agents and multi-agent workflows with support for Python and .NET.
Choose when you want a Python multi-agent orchestration framework with an enterprise deployment focus.
The Enterprise-Grade Multi-Agent Orchestration Framework. Website: https://swarms.ai
Choose when you want a Python agent platform with built-in runtime and management.
Build, run, and manage agent platforms.
Choose when you want role-playing, crew-style multi-agent orchestration in Python.
Framework for orchestrating role-playing, autonomous AI agents. By fostering collaborative intelligence, CrewAI empowers agents to work together seamlessly, tackling complex tasks.
Solves the same problem with a different architecture or at a different layer. Expect to rewrite the integration.
Choose when you need graph-based stateful orchestration and checkpointing instead of conversation-centric agents.
Build resilient agents.
Choose when adding agent capabilities to existing .NET/Python apps with a broader plugin and planner ecosystem.
Integrate cutting-edge LLM technology quickly and easily into your apps
Choose when you need a production-oriented multi-agent harness with monitoring rather than a conversation framework.
Multi-Agent Harness for Production AI
Choose when you need a Java enterprise workflow platform for building and deploying SuperAgents.
Enterprise-grade, commercial-friendly agentic workflow platform for building next-generation SuperAgents.
Choose when you need event-driven multi-agent integration with external data sources and enterprise systems.
An event-driven framework designed to build and orchestrate multi-agent AI systems. It enables seamless integration of AI agents with real-world data sources and systems, facilitating complex, multi-step workflows.
Choose when you want a Rust-core runtime with a Python API for high-throughput multi-agent workflows.
GraphBit is the world’s first enterprise-grade Agentic AI framework, built on a Rust core with a Python wrapper for unmatched speed, security, and scalability. It enables reliable multi-agent workflows with minimal CPU and memory usage, making it production-ready for real-world enterprise environments.
Choose when you want a batteries-included deep-agent harness layered on LangGraph patterns.
The batteries-included agent harness.
Choose when you prefer a TypeScript agent framework/platform instead of Python.
AI Agent Engineering Platform built on an Open Source TypeScript AI Agent Framework
Choose when you need a Java framework for distributed, long-running multi-agent systems.
Build distributed, production-grade, long-running agents.
Choose when you need a persistent, self-evolving multi-agent ecosystem rather than a stateless conversation framework.
The Harness of Harnesses: a trusted, persistent, self-evolving multi-agent ecosystem for all-domain collaboration.
Choose when you want a TypeScript runtime/harness layer to turn LLMs into production agents.
The open-source agent harness - the runtime layer that turns an LLM into a working agent.
Choose when you need a Go-native, event-driven agent framework with MCP tool discovery.
Open-source Agentic AI framework in Go for building, orchestrating, and deploying intelligent agents. LLM-agnostic, event-driven, with multi-agent workflows, MCP tool discovery, and production-grade observability.
Choose when you need to orchestrate existing coding-agent harnesses with policy and sandboxing rather than build agents from scratch.
Omnigent is an open-source AI agent framework and meta-harness: orchestrate Claude Code, Codex, Cursor, Pi, and custom agents — swap harnesses without rewriting, enforce policies and sandboxing, and collaborate in real time from any device.
Choose when you want a Python/TypeScript harness SDK that targets any model and cloud.
Build an agent harness and control it end-to-end. Open-source SDK for production AI agents in Python & TypeScript - any model, any cloud.
Choose when you need a Java/Spring-native agentic AI framework for enterprise apps.
Agentic AI Framework for Java Developers
Choose when you want a low-code Python multi-agent framework for quickly deploying autonomous workflows.
PraisonAI 🦞 — Hire a 24/7 AI Workforce. Stop writing boilerplate and start shipping autonomous self-improving agents that research, plan, code, and execute tasks. Deployed in 5 lines of code with built-in memory, RAG, and support for 100+ LLMs.
Choose when you want to build agents around Model Context Protocol with simple workflow patterns.
Build effective agents using Model Context Protocol and simple workflow patterns
Choose when you need modular RAG/LLM pipelines with explicit retrieval and routing control.
Open-source AI orchestration framework for building context-engineered, production-ready LLM applications. Design modular pipelines and agent workflows with explicit control over retrieval, routing, memory, and generation. Built for scalable agents, RAG, multimodal applications, semantic search, and conversational systems.
These projects were analysed and named ag2 among their alternatives. The relationship is not symmetric — how ag2 rates them is a separate judgement, made when ag2 is analysed in its own right.
calls ag2 “Use as a drop-in, actively maintained continuation of AutoGen under Apache-2.0.”
A programming framework for agentic AI
calls ag2 “mature production-oriented Python multi-agent framework and direct peer of CAMEL”
🐫 CAMEL: The first and the best multi-agent framework. Finding the Scaling Law of Agents. https://www.camel-ai.org
calls ag2 “choose if you want the AutoGen lineage with an all-in-one agent OS.”
A framework for building, orchestrating and deploying AI agents and multi-agent workflows with support for Python and .NET.
calls ag2 “when you want an AutoGen-derived conversation-first multi-agent framework with an established community”
The Enterprise-Grade Multi-Agent Orchestration Framework. Website: https://swarms.ai
calls ag2 “General-purpose multi-agent framework (formerly AutoGen); choose if you want a lower-level agent OS for custom workflows, not a built-in software-company pipeline.”
🌟 The Multi-Agent Framework: First AI Software Company, Towards Natural Language Programming
calls ag2 “formerly AutoGen, conversational multi-agent framework; choose for human-in-the-loop agent conversations.”
Open-source AI orchestration framework for building context-engineered, production-ready LLM applications. Design modular pipelines and agent workflows with explicit control over retrieval, routing, memory, and generation. Built for scalable agents, RAG, multimodal applications, semantic search, and conversational systems.
calls ag2 “Python continuation of AutoGen (AgentOS); choose if you are already in the AutoGen ecosystem and want a community-driven evolution.”
Agentic AI Framework for Java Developers
calls ag2 “Open-source AgentOS (formerly AutoGen); choose for a mature conversation-driven agent framework.”
Build effective agents using Model Context Protocol and simple workflow patterns
calls ag2 “choose when you need the AutoGen-derived AgentOS with multi-agent conversation patterns.”
⚙️🦀 Build modular and scalable LLM Applications in Rust
calls ag2 “Use for conversation-driven multi-agent collaboration from the AutoGen lineage; seed is not conversation-centric.”
Build an agent harness and control it end-to-end. Open-source SDK for production AI agents in Python & TypeScript - any model, any cloud.
calls ag2 “Choose when you want the open-source Python AG2/AutoGen multi-agent conversation stack instead of a Java-oriented runtime.”
Build distributed, production-grade, long-running agents.
calls ag2 “Choose it when you want AutoGen-style Python multi-agent conversations and an agent OS, accepting a Python runtime instead of Go.”
Open-source Agentic AI framework in Go for building, orchestrating, and deploying intelligent agents. LLM-agnostic, event-driven, with multi-agent workflows, MCP tool discovery, and production-grade observability.