MetaGPT: the framework that simulates a software company

“Code = SOP(Team)”: a software company in miniature

MetaGPT’s idea fits in its motto: apply standard operating procedures (SOPs) to a team made of agents. You give a one-line requirement, say “create a 2048 game”, and agents playing product manager, architect, project manager and engineer take turns producing user stories, competitive analysis, requirements, data structures, APIs, documents and code. It is a vivid example of a multi-agent system in which each role gets a precise job and hands its output to the next one, much like a real team.

The framework also offers standalone agents, notably the Data Interpreter, which writes and runs code to analyze data, as well as use cases such as agent debates, research and a receipt assistant. The team also publishes research, such as AFlow on automatically generating agent workflows, selected for an oral presentation at ICLR 2025.

Getting started

Install it with pip (pip install --upgrade metagpt) or with Docker. An init command creates a configuration file in your home folder, where you set the model provider, the model name and your API key. Then a single metagpt command followed by your request generates a full repository in a workspace folder. You can also use the framework as a Python library. An online demo hosted on Hugging Face lets you see the concept without installing anything.

Strengths and limits

Strengths. MIT license, a very concrete demonstration of agent teamwork, research roots, and support for several model providers as well as local models.

Limits. Development has slowed sharply since 2024, while the team focuses on its commercial product, Atoms. The Python version constraint (below 3.12) makes installation awkward on a recent machine. In practice, as with any AI-written code, a project generated end to end needs a careful review before real use. Official MCP support is not documented in the repository.

Alternatives

For everyday agentic coding, actively maintained tools such as OpenHands or Aider are a better fit. For collaboration between role-based agents, CrewAI leans toward production and CAMEL toward research.

Official repository: github.com/FoundationAgents/MetaGPT.