CrewAI

CrewAI is one of the most widely used open-source frameworks for building multi-agent AI systems in Python. Released in 2023 and distributed under the MIT license, it lets developers turn a set of large language model calls into a coordinated team of agents that collaborate on complex tasks, and it has grown into a standard starting point for engineering teams building agentic automation.

The framework is organized around two complementary ideas. Crews are teams of autonomous, role-based agents: each agent is defined by a role, a goal, and a backstory, and can be given its own model, tools, memory, and reasoning, after which the agents delegate to and consult one another to solve a task. Flows are event-driven workflows that manage state and give precise, deterministic control over how execution moves from step to step. In practice teams combine the two, using a Flow as the backbone of an application and dropping a Crew into a step when a problem needs open-ended, autonomous teamwork.

CrewAI is model-agnostic and ships with hundreds of built-in tools, from web search and website browsing to vector-database queries and code execution. It has first-class support for the Model Context Protocol, including custom MCP servers, the A2A protocol for agent-to-agent collaboration, and sandboxed code execution through E2B and Daytona. A production-oriented memory system goes beyond simple retrieval to resolve contradictions and recognize when it lacks context, and checkpointing lets developers replay, fork, and re-run workflows without starting over.

For teams running agents in production, CrewAI offers a commercial layer, the AMP Suite, built around a Control Plane that sits in the execution path of every workflow. It adds real-time tracing of each LLM and tool call with cost accounting, role-based access control and immutable audit trails, human-in-the-loop approval gates, runtime hooks for PII redaction and policy checks, evaluation, and agent training that turns production runs into improvement data. It can be deployed in the cloud or on premises and is used across a large share of the Fortune 500.