FoundationAgents/MetaGPT

Project overview

The framework applies standard operating procedures to LLM-based multi-agent teams, translating one-line requirements into structured software engineering deliverables.

Project type

AI Agent

Deployment

Refer to project documentation

License

MIT

Best for

• Developers seeking to automate structured software engineering workflows using a collaborative multi-agent LLM team.

Key capabilities

• Assigns different roles to GPTs, such as product managers, architects, project managers, and engineers, to form a collaborative entity for complex tasks.
• Provides a Data Interpreter role to write code for data analysis tasks.

Limitations and risks

• A configured LLM API service (e.g., OpenAI, Azure, Ollama, Groq) is strictly required, meaning local orchestration does not provide a local-only data boundary.
• Depending on the configured API, a paid service may be required.

Getting started

• Setup difficulty is rated medium and requires a Python environment configuration alongside a configured LLM such as gpt-4-turbo, gpt-3.5-turbo, or Ollama models.

Evidence and sources

Open original GitHub project