--- title: "MetaGPT" type: "tool" slug: "foundationagents-metagpt" canonical_url: "https://www.graphcanon.com/tools/foundationagents-metagpt" github_url: "https://github.com/FoundationAgents/MetaGPT" homepage_url: "https://atoms.dev/" stars: 69249 forks: 8830 primary_language: "Python" license: "MIT" categories: ["llm-frameworks", "ai-agents"] tags: ["multi-agent", "llm", "metagpt", "gpt", "agent"] updated_at: "2026-07-07T19:00:50.018468+00:00" --- # MetaGPT > MetaGPT: The Multi-Agent Framework A framework for assigning roles to AI agents with GPT capabilities, enabling them to collaborate on complex tasks akin to the operations of a software company. ## Facts - Repository: https://github.com/FoundationAgents/MetaGPT - Homepage: https://atoms.dev/ - Stars: 69,249 · Forks: 8,830 · Open issues: 132 · Watchers: 910 - Primary language: Python - License: MIT - Last pushed: 2026-01-21T10:12:33+00:00 ## Categories - [LLM Frameworks](/categories/llm-frameworks.md) - [AI Agents](/categories/ai-agents.md) ## Tags multi-agent, llm, metagpt, gpt, agent ## Related tools - [ECC](/tools/affaan-m-ecc.md) - The agent harness performance optimization system (★ 226,962) - [hermes-agent](/tools/nousresearch-hermes-agent.md) - The self-improving AI agent built by Nous Research (★ 210,880) - [AutoGPT](/tools/significant-gravitas-autogpt.md) - AutoGPT: Build, Deploy, and Run AI Agents (★ 185,417) - [ollama](/tools/ollama-ollama.md) - Get up and running with Kimi-K2.6, GLM-5.1, MiniMax, DeepSeek, gpt-oss, Qwen, Gemma and other models. (★ 175,659) - [prompts.chat](/tools/f-prompts-chat.md) - The world's largest open-source prompt library for AI (★ 165,019) - [transformers](/tools/huggingface-transformers.md) - 🤗 Transformers: the model-definition framework for state-of-the-art machine learning models (★ 162,347) - [langflow](/tools/langflow-ai-langflow.md) - Langflow is a powerful platform for building and deploying AI-powered agents and workflows. (★ 151,298) - [dify](/tools/langgenius-dify.md) - Production-ready platform for agentic workflow development (★ 148,070) ## README (excerpt) ```text # MetaGPT: The Multi-Agent Framework

MetaGPT logo: Enable GPT to work in a software company, collaborating to tackle more complex tasks.

[ En | 中 | Fr | 日 ] Assign different roles to GPTs to form a collaborative entity for complex tasks.

License: MIT Discord Follow Twitter Follow

## News 🚀 Mar. 10, 2025: 🎉 [mgx.dev](https://mgx.dev/) is the #1 Product of the Week on @ProductHunt! 🏆 🚀 Mar.   4, 2025: 🎉 [mgx.dev](https://mgx.dev/) is the #1 Product of the Day on @ProductHunt! 🏆 🚀 Feb. 19, 2025: Today we are officially launching our natural language programming product: [MGX (MetaGPT X)](https://mgx.dev/) - the world's first AI agent development team. More details on [Twitter](https://x.com/MetaGPT_/status/1892199535130329356). 🚀 Feb. 17, 2025: We introduced two papers: [SPO](https://arxiv.org/pdf/2502.06855) and [AOT](https://arxiv.org/pdf/2502.12018), check the [code](examples)! 🚀 Jan. 22, 2025: Our paper [AFlow: Automating Agentic Workflow Generation](https://openreview.net/forum?id=z5uVAKwmjf) accepted for **oral presentation (top 1.8%)** at ICLR 2025, **ranking #2** in the LLM-based Agent category. 👉👉 [Earlier news](docs/NEWS.md) ## Software Company as Multi-Agent System 1. MetaGPT takes a **one line requirement** as input and outputs **user stories / competitive analysis / requirements / data structures / APIs / documents, etc.** 2. Internally, MetaGPT includes **product managers / architects / project managers / engineers.** It provides the entire process of a **software company along with carefully orchestrated SOPs.** 1. `Code = SOP(Team)` is the core philosophy. We materialize SOP and apply it to teams composed of LLMs.

Software Company Multi-Agent Schematic (Gradually Implementing)

## Get Started ### Installation > Ensure that Python 3.9 or later, but less than 3.12, is installed on your system. You can check this by using: `python --version`. > You can use conda like this: `conda create -n metagpt python=3.9 && conda activate metagpt` ```bash pip install --upgrade metagpt # or `pip install --upgrade git+https://github.com/geekan/MetaGPT.git` # or `git clone https://github.com/geekan/MetaGPT && cd MetaGPT && pip install --upgrade -e .` ``` **Install [node](https://nodejs.org/en/download) and [pnpm](https://pnpm.io/installation#using-npm) before actual use.** For detailed installation guidance, please refer to [cli_install](https://docs.deepwisdom.ai/main/en/guide/get_started/installation.html#install-stable-version) or [docker_install](https://docs.deepwisdom.ai/main/en/guide/get_started/installation.html#install-with-docker) ### Configuration You can init the config of MetaGPT by running the following command, or manually create `~/.metagpt/config2.yaml` file: ```bash # Check https://docs.deepwisdom.ai/main/en/guide/get_started/configuration.html for more details metagpt --init-config # it will create ~/.metagpt/config2.yaml, just modify it to your needs ``` You can configure `~/.metagpt/config2.yaml` according to the [example](https://github.com/geekan/MetaGPT/blob/main/config/config2.example.yaml) and [doc](https://docs.deepwisdom.ai/main/en/guide/get_started/configuration.html): ```yaml llm: api_type: "openai" # or azure / ollama / groq etc. Check LLMType for more options model: "gpt-4-turbo ``` --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/tools/foundationagents-metagpt`](/api/graphcanon/tools/foundationagents-metagpt) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_