Practical overview
When it fits
Use it when a project needs coordinated agent collaboration, role-based task execution, or event-driven control over multiple LLM-powered steps. It is especially relevant when you want a Python framework rather than a ready-made end-user agent.
Who it is for
- Python developers building multi-agent applications
- Teams designing role-based agent collaboration
- Engineers creating event-driven LLM workflows
- Developers implementing production-oriented agent systems
Documented uses
- Assign complementary roles to autonomous agents working on a shared task.
- Coordinate agent steps through event-driven workflows.
- Break complex work into tasks handled by collaborative agent teams.
- Combine multi-agent orchestration with individual LLM calls.
- Build and run framework-based workflows in self-hosted or server environments.
Requirements & limits
The project is publicly available as open-source software under the MIT license. Supported contexts include Linux, macOS, Windows, CLI, server, and self-hosted environments.
- Crews and Flows address different orchestration needs: collaborative agent teams versus event-driven workflow control.
- The project is implemented in Python.
- Low-level APIs are available alongside higher-level abstractions.
- Its framework approach suits developers building their own workflows rather than users seeking a finished standalone agent.
- The MIT license may matter when evaluating how the project can be incorporated into a software build.
Check current requirements in the official documentation. Source-based guidance does not mean OpenViST has run or independently tested this project.
Scaffold a classic CrewAI crew project
Create the older Python/YAML CrewAI project structure.
Before you start
- A working CrewAI CLI installation
- A project name
Steps
Run
crewai create crew --classic.Use the generated project structure containing
crew.py,config/agents.yaml, andconfig/tasks.yamlas the classic scaffold.
Expected outcome
A classic CrewAI project scaffold is created with Python and YAML configuration files.
Guide limitations
- The evidence documents scaffolding only, not configuration or execution of the classic project.
- The classic scaffold is identified as the older Python/YAML format.
Compare options for Agent orchestration
These projects document a common task and share a project role. This is a source-based comparison, not an execution benchmark or a guarantee of interchangeability.
| Project | Documented purpose | Platform | Access and requirements |
|---|---|---|---|
| Crewai | Assign complementary roles to autonomous agents working on a shared task. | CLI, Linux, macOS, Self-hosted | The project is publicly available as open-source software under the MIT license. Supported contexts include Linux, macOS, Windows, CLI, server, and self-hosted environments. |
| Agenite | Define typed tools with JSON Schema validation and error handling. | CLI | |
| Veldra | Create an agent with a policy, tools, skills, knowledge base and reasoning method. | Self-hosted | The documented deployment is self-hosted and uses a sign-in gate after a first-run administrator account is created. |
Sources & review
Source record details
- Source availability
- Active
- Sources checked
- 30 September 2026
- Original website title
- crewAIInc/crewAI · Official homepage title · retained in its source language