Home / AI Agent Frameworks / Best AI Agent Frameworks for Multi-Agent Systems
Best AI Agent Frameworks for Multi-Agent Systems
Need multiple AI agents collaborating? These frameworks provide the best orchestration, role assignment, and inter-agent communication capabilities.
#1
Agency Swarm
Python
MIT
Intermediate
Multi-agent orchestration framework extending OpenAI SDK
Ease of Use4/5
Scalability3/5
Documentation3/5
Community3/5
Performance4/5
#2
SwarmZero
Python
Proprietary
Intermediate
AI agent marketplace and orchestration platform
Ease of Use3/5
Scalability3/5
Documentation3/5
Community3/5
Performance3/5
#3
Dify
Python
Apache-2.0
Intermediate
Production-ready platform for LLMOps and agent development
Ease of Use4/5
Scalability5/5
Documentation5/5
Community5/5
Performance4/5
#4
OpenAI AgentKit
Agent Framework|Enterprise Integration
Agent primitives|Handoffs|Guardrails|Tracing
MIT
Production framework for building enterprise AI agents
Ease of Use3/5
Scalability4/5
Documentation5/5
Community5/5
Performance5/5
#5
CrewAI
Python
MIT
Intermediate
Framework for orchestrating role-playing autonomous AI agents
Ease of Use4/5
Scalability4/5
Documentation4/5
Community5/5
Performance4/5
#6
LangGraph
Python
MIT
Advanced
Low-level orchestration framework for stateful multi-agent systems
Ease of Use3/5
Scalability5/5
Documentation4/5
Community4/5
Performance5/5
#7
ControlFlow
Python
Apache-2.0
Intermediate
Task-centric agent framework from Prefect
Ease of Use4/5
Scalability4/5
Documentation4/5
Community3/5
Performance4/5
Compare all 40+ frameworks
Interactive comparison table with filters, scores, and head-to-head matchups.
View All Frameworks