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CrewAI Documentation

Build with AI

Build with AI

Section titled “Build with AI”

CrewAI is AI-native. This page brings together everything an AI coding agent needs to build with CrewAI — whether you’re Claude Code, Codex, Cursor, Gemini CLI, or any other assistant helping a developer ship crews and flows.

Supported Coding Agents

Section titled “Supported Coding Agents”

Claude Code

Cursor

Codex

Windsurf

Gemini CLI

1. Skills — Teach Your Agent CrewAI

Section titled “1. Skills — Teach Your Agent CrewAI”

Skills are instruction packs that give coding agents deep CrewAI knowledge — how to scaffold Flows, configure Crews, use tools, and follow framework conventions.

Claude Code (Plugin Marketplace)
Anthropic

CrewAI skills are available in the Claude Code plugin marketplace — the same distribution channel used by top AI-native companies:

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

Four skills activate automatically when you ask relevant CrewAI questions:

SkillWhen it runs
getting-startedScaffolding new projects, choosing between LLM.call() / Agent / Crew / Flow, wiring crew.jsonc / 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
npx (Any Agent)

Works with Claude Code, Codex, Cursor, Gemini CLI, or any coding agent:

Terminal window
npx skills add crewaiinc/skills

Pulls from the skills.sh registry.

  1. Install the official skill pack

    Use either method above — the Claude Code plugin marketplace or npx skills add. Both install the official crewAIInc/skills pack.

  2. Your agent gets instant CrewAI expertise

    The skill pack teaches your agent:

    • Flows — stateful apps, steps, and crew kickoffs
    • Crews & Agents — JSON-first patterns (crew.jsonc, agents/*.jsonc), roles, tasks, delegation
    • Tools & Integrations — search, APIs, MCP servers, and common CrewAI tools
    • Project layout — CLI scaffolds and repo conventions
    • Up-to-date patterns — tracks current CrewAI docs and best practices
  3. Start building

    Your agent can now scaffold and build CrewAI projects without you re-explaining the framework each session.

Skills concept

How skills work in CrewAI agents — injection, activation, and patterns.

Skills landing page

Overview of the crewAIInc/skills pack and what it includes.

AGENTS.md & coding tools

Set up AGENTS.md for Claude Code, Codex, Cursor, and Gemini CLI.

Skills registry (skills.sh)

Official listing — skills, install stats, and audits.

2. llms.txt — Machine-Readable Docs

Section titled “2. llms.txt — Machine-Readable Docs”

CrewAI publishes an llms.txt file that gives AI assistants direct access to the full documentation in a machine-readable format.

https://docs.crewai.com/llms.txt
What is llms.txt?

llms.txt is an emerging standard for making documentation consumable by large language models. Instead of scraping HTML, your agent can fetch a single structured text file with all the content it needs.

CrewAI’s llms.txt is already live — your agent can use it right now.

How to use it

Point your coding agent at the URL when it needs CrewAI reference docs:

Fetch https://docs.crewai.com/llms.txt for CrewAI documentation.

Many coding agents (Claude Code, Cursor, etc.) can fetch URLs directly. The file contains structured documentation covering all CrewAI concepts, APIs, and guides.

Why it matters
  • No scraping required — clean, structured content in one request
  • Always up-to-date — served directly from docs.crewai.com
  • Optimized for LLMs — formatted for context windows, not browsers
  • Complements skills — skills teach patterns, llms.txt provides reference

3. Deploy to Enterprise

Section titled “3. Deploy to Enterprise”

Go from a local crew to production on CrewAI AMP (Agent Management Platform) in minutes.

  1. Build locally

    Scaffold and test your crew or flow:

    Terminal window
    crewai create crew my_crew
    cd my_crew
    crewai run
  2. Prepare for deployment

    Ensure your project structure is ready:

    Terminal window
    crewai deploy --prepare

    See the preparation guide for details on project structure and requirements.

  3. Deploy to AMP

    Push to the CrewAI AMP platform:

    Terminal window
    crewai deploy

    You can also deploy via GitHub integration or Crew Studio.

  4. Access via API

    Your deployed crew gets a REST API endpoint. Integrate it into any application:

    Terminal window
    curl -X POST https://app.crewai.com/api/v1/crews/<crew-id>/kickoff \
      -H "Authorization: Bearer $CREWAI_API_KEY" \
      -H "Content-Type: application/json" \
      -d '{"inputs": {"topic": "AI agents"}}'

Deploy to AMP

Full deployment guide — CLI, GitHub, and Crew Studio methods.

AMP introduction

Platform overview — what AMP provides for production crews.

4. Enterprise Features

Section titled “4. Enterprise Features”

CrewAI AMP is built for production teams. Here’s what you get beyond deployment.

Observability

Detailed execution traces, logs, and performance metrics for every crew run. Monitor agent decisions, tool calls, and task completion in real time.

Crew Studio

No-code/low-code interface to create, customize, and deploy crews visually — then export to code or deploy directly.

Webhook Streaming

Stream real-time events from crew executions to your systems. Integrate with Slack, Zapier, or any webhook consumer.

Team Management

SSO, RBAC, and organization-level controls. Manage who can create, deploy, and access crews across your team.

Tool Repository

Publish and share custom tools across your organization. Install community tools from the registry.

Factory (Self-Hosted)

Run CrewAI AMP on your own infrastructure. Full platform capabilities with data residency and compliance controls.

Who is AMP for?

AMP is for teams that need to move AI agent workflows from prototypes to production — with observability, access controls, and scalable infrastructure. Whether you’re a startup or enterprise, AMP handles the operational complexity so you can focus on building agents.

What deployment options are available?
  • Cloud (app.crewai.com) — managed by CrewAI, fastest path to production
  • Factory (self-hosted) — run on your own infrastructure for full data control
  • Hybrid — mix cloud and self-hosted based on sensitivity requirements

Explore CrewAI AMP →

Sign up and deploy your first crew to production.