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Side-by-side comparison

AutoGen vs CrewAI

AutoGen

Build multi-agent AI workflows that can act and collaborate

AgenticnessAdaptive Collaborator
vs
CrewAI

Build and scale collaborative AI agent workflows

AgenticnessGuided Assistant

Side-by-side comparison based on our agenticness evaluation framework

At a glance

Quick Facts

FeatureAutoGenCrewAI
CategoryMulti-Agent Orchestration, Agent Frameworks & OrchestrationMulti-Agent Orchestration, Agent Frameworks & Orchestration
DeploymentSelf-hostedHybrid (cloud + self-hosted)
Autonomy LevelSemi-autonomousSemi-autonomous
Model SupportMulti-modelSingle model
Open SourceYesYes
MCP SupportYes--
Team SupportSmall teamEnterprise
Pricing ModelFree / open sourceFreemium
Interfaceapi, gui, cligui, web, api
32-point evaluation

Agenticness

12/32
Adaptive Collaborator
AutoGen
8/32
Guided Assistant
CrewAI

Dimension Breakdown (0-4 each)

Action Capability
AutoGen
3
CrewAI
2
Autonomy
AutoGen
2
CrewAI
1
Planning
AutoGen
2
CrewAI
1
Adaptation
AutoGen
1
CrewAI
0
State & Memory
AutoGen
1
CrewAI
0
Reliability
AutoGen
0
CrewAI
1
Interoperability
AutoGen
2
CrewAI
1
Safety
AutoGen
1
CrewAI
2

Scores from our agenticness evaluation framework. Higher is more autonomous.

Features & Use Cases

AutoGen

Features

  • Builds multi-agent AI applications
  • Provides a low-level Core API for message passing and event-driven agents
  • Includes AgentChat for higher-level multi-agent patterns
  • Supports extensions for model clients and tools
  • Can connect to MCP servers for external tool use
  • Works with OpenAI models in the quickstart examples
  • Includes AutoGen Studio for no-code workflow prototyping
  • Supports browser-based workflows through Playwright MCP

Use Cases

  • Developing custom multi-agent assistants for internal workflows
  • Prototyping agent workflows without writing code in AutoGen Studio
  • Building tool-using assistants that can browse the web through MCP
  • Orchestrating expert sub-agents for tasks like math, research, or domain-specific reasoning
  • Extending existing applications with agent behavior and external integrations
CrewAI

Features

  • Visual editor for building agentic workflows
  • AI copilot for workflow creation
  • Integrated tools and triggers
  • Workflow execution limits by plan
  • Cloud SaaS deployment
  • Self-hosted deployment via Kubernetes and VPC for Enterprise
  • SSO for Enterprise
  • Secret manager integration for Enterprise

Use Cases

  • Teams building production AI agent workflows with a visual interface
  • Organizations that want to deploy agents in a managed cloud environment
  • Enterprises that need self-hosted agent infrastructure on private cloud or on-prem systems
  • Developers who want to prototype an agent workflow and later scale it for production

Pricing

AutoGen
- **Free:** Open-source framework; pricing details for hosted services or paid tiers are not publicly available in the provided content. - **Pro:** Not publicly available. - **Enterprise:** Not publicly available.
CrewAI
- **Free (Basic):** Free tier with a visual editor, AI copilot, integrated tools and triggers, and 50 workflow executions per month. - **Professional ($25/month):** Includes everything in Basic, plus 1 additional seat, 100 workflow executions per month, and support via the community forum. - **Enterprise:** Custom pricing. Includes SaaS or self-hosted deployment via Kubernetes and VPC, SOC2, SSO, secret manager integration, PII detection and masking, dedicated support, uptime SLAs, Slack or Teams support channels, and forward-deployed engineers.
Analysis

Our Verdict

If you’re building a truly custom, code-driven multi-agent architecture—especially one that must orchestrate specialized sub-agents and connect out to MCP servers (including browser workflows via Playwright)—pick AutoGen. If your team wants a production workflow platform with a visual builder, an AI copilot for creating workflows, and straightforward scaling from a free Basic tier through paid plans—pick CrewAI AMP; and if you specifically need enterprise governance (Kubernetes/VPC self-hosting, SSO, secret management, PII masking, SLAs), CrewAI AMP is the better fit.

Choose AutoGen if...

  • +Choose AutoGen if you want a developer framework to *build custom multi-agent systems* with fine-grained control over agent-to-agent interaction, using its Core runtime and higher-level AgentChat API to orchestrate workflows.
  • +Choose AutoGen if you need to connect agents to external tool ecosystems via *MCP servers*—including examples that show MCP integrations and Playwright-based browser workflows for tool-using, web-aware agents.
  • +Choose AutoGen if you prefer to *prototype and iterate by coding* (Python 3.10+ + pip) and optionally use AutoGen Studio for no-code workflow prototyping, rather than starting from a managed platform workflow editor.

Choose CrewAI if...

  • +Choose CrewAI AMP if your priority is moving from prototype to production using a *visual editor* and an end-to-end workflow platform with execution limits, so teams can build and test workflows without hand-wiring everything in code.
  • +Choose CrewAI AMP if you want *managed cloud deployment by default*, with a clear upgrade path (Basic free tier → Professional → Enterprise) and team-oriented controls like seats and workflow-execution-based pricing.
  • +Choose CrewAI AMP if you have enterprise requirements such as *self-hosted deployment on Kubernetes/VPC*, SSO, secret manager integration, and Enterprise-grade controls like PII detection/masking and uptime SLAs.