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
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:
| Skill | When it runs |
|---|
getting-started | Scaffolding new projects, choosing between LLM.call() / Agent / Crew / Flow, wiring crew.jsonc / main.py |
design-agent | Configuring agents — role, goal, backstory, tools, LLMs, memory, guardrails |
design-task | Writing task descriptions, dependencies, structured output (output_pydantic, output_json), human review |
ask-docs | Querying 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?
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
Setup and run your first CrewAI agents by following this tutorial.
Learning Resources
Learn CrewAI through our comprehensive courses:
This is the beginning of the README. Read the rest at the original. Read the full README ↗
