CrewAI

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 Repository   47,090  6,365
Orchestrating role-playing autonomous AI agents for collaborative task execution
multi-agent role-playing collaborative-agents orchestration task-execution
TypeFramework
HostingHybrid
MaturityStable
Status Maintained

Key Features

Multi-Agent Single Agent Human-in-the-Loop Streaming Async Support Short-Term Memory Long-Term Memory Shared Memory Plugin System Custom Tools MCP Protocol A2A Protocol Code Execution Self-Hosted Cloud Hosted

Community Feedback

  Strengths

  • Intuitive role-based abstraction
  • Minimal code for multi-agent pipelines
  • Best starting framework for multi-agent
  • Mature ecosystem

  Weaknesses

  • Common case trivial but uncommon harder
  • Lacks native file persistence
  • Less flexible than LangGraph for complex flows

CrewAI Details

OrganizationCrewAI Inc
Organization TypeCompany
FundingSeries a
CategoryFramework
SubcategoryMulti agent
DeploymentHybrid
Primary LanguagePython
RuntimePython 3.10+
LicenseMIT
Commercial UseUnrestricted
Install Commandpip install crewai
GitHub Stars47,090
GitHub Forks6,365
Release CadenceBiweekly
MaturityStable
Pricing ModelOpen core
Free TierMIT-licensed core is free
Self-Hosted FreeYes
Cost Modelfree + LLM costs
Community SizeVery large
Community ActivityVery active
Sentiment Very positive
GPU RequiredNo
Research Date2026-03-24
LLM ProvidersOpenAI, Anthropic, Google, Mistral, Ollama, local models
API Keys RequiredLLM provider API key

Use Cases

When to Use

Best for: Teams starting with multi-agent systems who want role-based abstractions

Avoid when: Highly custom agent communication patterns are needed

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Release v20260328a