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CrewAI

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#2 Python agent framework — 5.7M PyPI downloads/month (3× growth in 6 months), Fortune 500 customers (PwC, IBM, Capgemini, NVIDIA, DocuSign), YAML-driven role-based orchestration rated 'fastest to prototype' in 2026 independent reviews. CVE-responsive: gitpython path traversal fixed in v1.11.0.

Score 93

Where it wins

5.7M PyPI downloads/month — 3× growth in 6 months

Named Fortune 500 customers: PwC, IBM, Capgemini, NVIDIA, DocuSign (multi-source confirmed)

YAML-driven config, role-based crew orchestration — consistently rated 'easiest to prototype with'

89 commits in last 30 days; v1.11.0 released 2026-03-18

Active CVE response — gitpython path traversal fixed in v1.11.0

Native A2A + MCP support (v1.10) — only major framework with both protocols

CrewAI AMP Suite: enterprise tracing, RBAC, unified control plane

Where to be skeptical

Observability less mature than LangGraph without AMP Suite — logs hide LLM decision details

Star-to-download gap: 46.6K stars but 123 DL/star vs LangGraph's 1,516 — hype > adoption signal

For complex long-running stateful workflows, LangGraph's architecture is more appropriate

Editorial verdict

Second-largest Python deployment footprint with real Fortune 500 adoption. Consistently rated 'fastest to prototype' — not marketing copy but backed by independent consensus. The right default for role-based business workflow automation teams prioritizing speed. Trade off: observability less mature than LangGraph without AMP Suite.

Videos

Reviews, tutorials, and comparisons from the community.

CrewAI Step-by-Step | Complete Course

Alejandro AO·2024

CrewAI Full Tutorial By Example

Kronecker AI·2025

Automate ANYTHING With AI Agent Teams

Matthew Berman·2025

Related

Claude Code

98

Anthropic's official agentic coding CLI. v2.1.81 (Mar 20) shipped `--bare`, smarter worktree resume, and improved MCP OAuth while the repo crossed 82,204 stars and logged ~14 commits/week across 10+ maintainers. Terminal-native, tool-use-driven, with deep file system + shell access, #1 SWE-bench Pro standardized (45.89%), ~4% of GitHub public commits (SemiAnalysis), $2.5B annualized revenue. 8M+ npm weekly downloads. Opus 4.6 with 1M context.

LangGraph

95

#1 Python agent framework by production evidence — 40.2M PyPI downloads/month, Fortune 500 deployments (LinkedIn, Uber, Replit, Elastic, Klarna, Cloudflare, Coinbase), ~400 LangGraph Platform companies, LangSmith rated best-in-class observability. Stable v1.x API, model-agnostic, MCP support.

Pydantic AI

95

#3 Python agent framework by downloads — 15.6M PyPI/month. Built by the Pydantic team. Runtime type enforcement is a genuine differentiator no other framework offers. V1 shipped with Temporal integration for durable execution and Logfire observability. Emerging pattern: 'Pydantic AI for agent logic, LangGraph for orchestration' (ZenML).

AutoGen (Microsoft)

95

⚠️ MAINTENANCE MODE — Microsoft officially confirmed bug fixes and security patches only, no new features (VentureBeat 2026-02-19). 55.9K stars but only 1.57M PyPI/month — DL/star ratio of 28, the most inflated among active frameworks. Being replaced by Microsoft Agent Framework (AutoGen + Semantic Kernel merge, GA targeted ~Q2 2026). Teams on AutoGen should plan migration.

Public evidence

Raw GitHub source

GitHub README peek

Constrained peek so you can sanity-check the source material without leaving the site.

<p align="center"> <a href="https://github.com/crewAIInc/crewAI"> <img src="https://raw.githubusercontent.com/crewAIInc/crewAI/main/docs/images/crewai_logo.png" width="600px" alt="Open source Multi-AI Agent orchestration framework"> </a> </p> <p align="center" style="display: flex; justify-content: center; gap: 20px; align-items: center;"> <a href="https://trendshift.io/repositories/11239" target="_blank"> <img src="https://trendshift.io/api/badge/repositories/11239" alt="crewAIInc%2FcrewAI | Trendshift" style="width: 250px; height: 55px;" width="250" height="55"/> </a> </p> <p align="center"> <a href="https://crewai.com">Homepage</a> · <a href="https://crewai.com/open-source">Open Source</a> · <a href="https://docs.crewai.com">Docs</a> · <a href="https://app.crewai.com">Start Cloud Trial</a> · <a href="https://blog.crewai.com">Blog</a> · <a href="https://community.crewai.com">Forum</a> </p> <p align="center"> <a href="https://github.com/crewAIInc/crewAI"> </a> <a href="https://github.com/crewAIInc/crewAI/network/members"> </a> <a href="https://github.com/crewAIInc/crewAI/issues"> </a> <a href="https://github.com/crewAIInc/crewAI/pulls"> </a> <a href="https://opensource.org/licenses/MIT"> </a> </p> <p align="center"> <a href="https://pypi.org/project/crewai/"> </a> <a href="https://pypi.org/project/crewai/"> </a> <a href="https://twitter.com/crewAIInc"> </a> </p>
Fast and Flexible Multi-Agent Automation Framework

CrewAI is an open-source Python framework with high-level abstractions and low-level APIs for building production-ready multi-agent workflows. It gives developers autonomous agent collaboration through Crews and precise, event-driven control through Flows.

  • CrewAI Crews: Optimize for autonomy and collaborative intelligence with role-based AI agents.
  • CrewAI Flows: Build event-driven automations that combine precise workflow control, single LLM calls, and native support for Crews.

With over 100,000 developers certified through our community courses at learn.crewai.com, CrewAI is rapidly becoming the standard for production-ready agentic automation.

CrewAI AMP Suite

For organizations that need a commercial control plane around CrewAI, CrewAI AMP Suite adds managed deployment, observability, governance, security, and enterprise support.

You can try one part of the suite, the Crew Control Plane, for free.

Crew Control Plane Key Features:

  • Tracing & Observability: Monitor and track your AI agents and workflows in real-time, including metrics, logs, and traces.
  • Unified Control Plane: A centralized platform for managing, monitoring, and scaling your AI agents and workflows.
  • Seamless Integrations: Easily connect with existing enterprise systems, data sources, and cloud infrastructure.
  • Advanced Security: Built-in robust security and compliance measures ensuring safe deployment and management.
  • Actionable Insights: Real-time analytics and reporting to optimize performance and decision-making.
  • 24/7 Support: Dedicated enterprise support to ensure uninterrupted operation and quick resolution of issues.
  • On-premise and Cloud Deployment Options: Deploy CrewAI AMP on-premise or in the cloud, depending on your security and compliance requirements.

CrewAI AMP is designed for enterprises seeking a powerful, reliable solution to transform complex business processes into efficient, intelligent automations.

Table of contents

  • Build with AI
  • Why CrewAI?
  • Getting Started
  • Key Features
  • Understanding Flows and Crews
  • Examples
    • Quick Tutorial
    • Write Job Descriptions
    • Trip Planner
    • Stock Analysis
    • Using Crews and Flows Together
  • Connecting Your Crew to a Model
  • When to Use CrewAI
  • Contribution
  • Telemetry
  • License
  • Frequently Asked Questions (FAQ)

Build with AI

Using an AI coding agent? Teach it CrewAI best practices in one command:

Claude Code:

/plugin marketplace add crewAIInc/skills
/plugin install crewai-skills@crewai-plugins
/reload-plugins

Four skills that activate automatically when you ask relevant CrewAI questions:

SkillWhen it runs
getting-startedScaffolding new projects, choosing between LLM.call() / Agent / Crew / Flow, wiring crew.py / main.py
design-agentConfiguring agents — role, goal, backstory, tools, LLMs, memory, guardrails
design-taskWriting task descriptions, dependencies, structured output (output_pydantic, output_json), human review
ask-docsQuerying the live CrewAI docs MCP server for up-to-date API details

Cursor, Codex, Windsurf, and others (skills.sh):

npx skills add crewaiinc/skills

This installs the official CrewAI Skills — structured instructions that teach coding agents how to scaffold Flows, configure Crews, design agents and tasks, and follow CrewAI patterns.

Why CrewAI?

<div align="center" style="margin-bottom: 30px;"> <img src="https://raw.githubusercontent.com/crewAIInc/crewAI/main/docs/images/asset.png" alt="CrewAI Logo" width="100%"> </div>

CrewAI unlocks the true potential of multi-agent automation, delivering speed, flexibility, and control through Crews of AI agents and event-driven Flows:

  • Purpose-built architecture: Designed specifically for agent orchestration, with a lightweight Python core and clean primitives for real-world automation.
  • High Performance: Optimized for speed and minimal resource usage, enabling faster execution.
  • Flexible Low-Level Customization: Complete freedom to customize everything from workflows and system architecture to agent behaviors, internal prompts, and execution logic.
  • Ideal for Every Use Case: Proven effective for simple tasks, complex workflows, and production-grade automation.
  • Robust Community: Backed by a rapidly growing community of over 100,000 certified developers offering comprehensive support and resources.

CrewAI empowers developers and teams to build intelligent automations that balance simplicity, flexibility, and production-grade control.

Getting Started

View on GitHub →