CrewAI: getting AI agents to work as a team

The idea: a team instead of a single agent

Rather than handing a whole job to one AI agent, CrewAI has you assemble a “crew”: say, a researcher agent, a writer agent and a reviewer agent. Each has a role, a goal and tools, and tasks are either chained or shared among them. The team metaphor makes the logic of a multi-agent system easy to follow, even for non-specialists.

The framework offers two complementary modes:

• Crews, for autonomy: agents collaborate based on their roles;
• Flows, for control: an event-driven agentic workflow with state, branching and predefined steps, which can call Crews.

Getting started

CrewAI runs on Python (versions 3.10 through 3.13 at the time of writing). The steps described in the official repository: install the command-line tool with uv, generate a project with crewai create crew, describe your agents and tasks in the generated configuration files, then launch everything with crewai run. You will need an API key for your chosen model, or a local model.

Strengths and limits

Strengths: a quick learning curve thanks to the role / task / crew vocabulary, a standalone framework with no LangChain dependency, freedom to choose your model, support for MCP to plug in external tools, and A2A support mentioned in the README.

Limits: the freedom given to agents in a Crew makes results less predictable than a strict sequence; Flows exist precisely to take back control. Several agents talking to each other also means more model calls, and therefore higher costs. Finally, CrewAI is Python only.

A commercial layer next to the open source project

The company sells CrewAI AMP Suite, a control plane for organizations: managed deployment, observability, governance, security and support, in the cloud or on-premises. As of October 22, 2026, the pricing page lists a free Basic plan (visual editor, AI copilot, 50 workflow executions per month) and an Enterprise plan priced on request.

Alternatives

If you need finer control over each step, LangGraph is the go-to option. In a Microsoft environment (.NET, Azure), Microsoft Agent Framework covers similar needs.