CrewAI

What is CrewAI?

CrewAI is a framework and hosted platform for building teams of AI agents that split up a job and work through it together. Developers install the Python package with uv, scaffold a project with the crewai CLI, and define agents and tasks in YAML or code, then run them as a crew or as a stateful Flow. The CrewAI AMP platform adds a visual Studio editor, tracing, guardrails, human-in-the-loop input, usage dashboards and REST endpoints for each deployed crew. Agents can use connected apps such as Gmail, Google Drive, HubSpot and Slack through OAuth, and workflows can be exported as an MCP server. Deployment options include CrewAI's cloud, a dedicated VPC, self-hosted Factory or a hybrid of the two. The vendor says 65% of the Fortune 500 use it. The core framework is open source under the MIT license. On the platform, the Basic plan is free with 50 workflow executions a month, and Enterprise pricing is custom.

Use cases

• Build a crew of cooperating agents
• Automate multi-step business workflows
• Deploy agents behind a REST API
• Trace and test agent runs
• Connect agents to Gmail and Slack
• Export a workflow as an MCP server
• Govern agents with SSO and RBAC

Who it's for

• Python developers
• AI engineers
• Enterprise IT teams
• Automation builders

Why use CrewAI

• Role, goal and task definitions map closely to how human teams divide work, so prototypes come together quickly.
• You can start in code with the open-source framework or in the no-code Studio editor on the same platform.
• Built-in tracing, guardrails and usage dashboards help you see what each agent did before going to production.
• Enterprise deployments can run in CrewAI's cloud, your own VPC or your own infrastructure.
• Official skills let coding assistants such as Claude Code or Cursor scaffold CrewAI projects for you.

CrewAI features

• Python framework with Crews, Agents, Tasks and Flows
• Studio visual editor with an AI copilot
• Tracing with OpenTelemetry support
• Guardrails and human-in-the-loop input
• OAuth app integrations such as Gmail, HubSpot and Slack
• Export workflows as an MCP server or UI component
• Usage dashboard with token counts and performance metrics
• SSO, role-based access control and audit trails on Enterprise
• Deploy to cloud, VPC or self-hosted Factory
• Agent skills pack for Claude Code, Codex, Cursor and Gemini CLI

CrewAI integrations

• Gmail
• Google Drive
• HubSpot
• Slack
• Okta
• GitHub
• Zapier

How to get started with CrewAI

1. Install the crewai CLI with uv tool install crewai, then run crewai create crew to scaffold a project.
2. Define agents and tasks in agents.yaml and tasks.yaml, add tools, and put your API keys in .env.
3. Run crewai install and crewai run to execute the crew locally and check the output.
4. Run crewai deploy to push the project to CrewAI AMP, which exposes a REST endpoint for the crew.
5. Monitor runs with traces, logs and the usage dashboard, and adjust agents as results come in.

CrewAI limitations

• Requires Python 3.10 or newer and below 3.14 for the framework
• Basic plan is capped at 50 workflow executions a month
• SSO, RBAC, enterprise connectors and dedicated VPC are Enterprise only
• Model costs come from whichever LLM provider you connect

CrewAI pricing

CrewAI is open source, so you can use and self-host it for free.

CrewAI plans

• Basic

  Free

  • Visual editor and AI copilot
  • GitHub integration
  • 50 workflow executions/month

• Enterprise

  Custom

  • SSO, RBAC, workload identity, PII redaction
  • Cloud, VPC or own infrastructure
  • 45-day onboarding
  • Forward deployed engineering available a la carte

Plans as listed on the official pricing page on 24 Oct 2026. Prices can change and may vary by country or exclude tax. Check the official pricing page.

CrewAI alternatives

The main CrewAI alternatives listed on Debuly are LangGraph, AutoGen, AG2, Agno, LlamaIndex and OpenAI Agents SDK. The table compares pricing and platforms; order is A–Z.

1. 

   AG2

   Open-source multi-agent framework, formerly AutoGen, plus an AgentOS platform for coordinating and deploying teams of AI agents.

   Developer platformsAutomation and agentsCoding
   Open sourceVisit AG2 (official site)
2. 

   Agno

   Python framework and AgentOS runtime for building agents, teams and workflows, then serving them as an API with a control plane.

   Developer platformsAutomation and agentsCoding
   Open sourceVisit Agno (official site)
3. 

   AutoGen

   Microsoft's MIT-licensed Python and .NET framework for multi-agent AI apps, now archived; new projects are pointed to Microsoft Agent Framework.

   Developer platformsAutomation and agentsCoding
   Open sourceVisit AutoGen (official site)
4. 

   LangGraph

   Low-level open-source orchestration framework and runtime for building stateful, long-running AI agents as graphs.

   Developer platformsAutomation and agentsCoding
   Open sourceVisit LangGraph (official site)
5. 

   LlamaIndex

   Open-source framework plus the LlamaParse platform for parsing, extracting and indexing documents so LLM apps can use them.

   Developer platformsResearch and searchAutomation and agents
   FreemiumVisit LlamaIndex (official site)
6. 

   OpenAI Agents SDK

   Open-source Python framework for building multi-agent workflows with tools, handoffs, guardrails, tracing, sandboxes and voice agents.

   Developer platformsAutomation and agentsCoding
   Open sourceVisit OpenAI Agents SDK (official site)

CrewAI FAQ

Sources & verification

Facts on this page come from the official sources below, each with the date we read it. Written by Debuly; the vendor did not review this page.

Image credits

• Logo: from crewai.com · fetched 23 Oct 2026 · Vendor trademark, used only to identify the product; removed on request
• Cover: none collected yet, so a generated tile is shown.

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