MetaGPT

We build cutting-edge multi-agent AI systems that automate complex tasks through intelligent collaboration. Key Highlights: · MetaGPT Open Source: Pioneering framework (github.com/geekan/MetaGPT) automating software development via AI agent teams using SOPs. Highly recognized in the open-source community. · MetaGPT X (MGX): Our commercial platform (mgx.dev) – an AI agent team available 24/7 via natural language to build websites, apps, and more. Awarded #1 on Product Hunt. · OpenManus: Extending multi-agent AI to accelerate scientific research workflows. · Research Leadership: Driving the field forward with foundational papers like "MetaGPT" (ICLR '24 Oral), "AFlow" (ICLR '25 Oral), and the comprehensive "Foundation Agents" survey (arXiv:2504.01990). We're shaping the future of AI-driven automation and human-AI collaboration.

Agent Framework

Visit Website

Founded

2025

Location

Palo Alto, CA

Employees

Funding

OSS

MetaGPT: Open‑Source Multi‑Agent “AI Dev Team” for Software Generation

MetaGPT is an open-source multi-agent framework and commercial platform that simulates a full software team. It assigns SOP-driven roles—product manager, architect, project manager, and engineer—to LLM agents to transform a single requirement into PRDs, designs, tasks, and code. The project lives on [GitHub](https://github.com/FoundationAgents/MetaGPT) with extensive documentation at the [MetaGPT docs](https://docs.deepwisdom.ai/main/en/guide/get_started/introduction.html). The hosted layer, **MetaGPT X (MGX)**, offers a guided “AI dev team” experience for non-technical users via [mgx.dev](https://mgx.dev).

Company: MetaGPT (HQ: Palo Alto; 11–50 employees per [LinkedIn](https://www.linkedin.com/company/metagpt))

Products: Open-source MetaGPT framework; MGX commercial platform

Positioning: SOP-driven orchestration for end-to-end software generation

Official resources: [Docs](https://docs.deepwisdom.ai/main/en/guide/get_started/introduction.html) • [GitHub](https://github.com/FoundationAgents/MetaGPT) • [Company site](https://www.deepwisdom.ai) • [MGX](https://mgx.dev)

What MetaGPT Does

MetaGPT automates common software lifecycle steps by coordinating specialized agents:

Product ideation to PRDs and competitive analysis

Architecture drafts, API specs, and design docs

Task planning and issue breakdowns

Repo scaffolding and starter code generation

Iterative improvements through SOP-driven workflows

The framework emphasizes repeatability and structure, producing artifacts like PRDs and diagrams from short prompts. Public guides (e.g., from IBM) demonstrate MetaGPT combined with local models for budget-friendly, self-hosted workflows—see IBM’s walkthrough on [PRD automation with MetaGPT + Ollama + DeepSeek](https://www.ibm.com/think/tutorials/multi-agent-prd-ai-automation-metagpt-ollama-deepseek).

Platform Components

Open-source framework

Access via [GitHub](https://github.com/FoundationAgents/MetaGPT)

Getting started in the [Quickstart](https://docs.deepwisdom.ai/main/en/guide/get_started/quickstart.html) and [Setup](https://docs.deepwisdom.ai/main/en/guide/get_started/setup.html)

Concepts and tutorials in [Multi‑Agent 101](https://docs.deepwisdom.ai/main/en/guide/tutorials/multi_agent_101.html)

Commercial: MetaGPT X (MGX)

A hosted “AI dev team” for app/website building and data analysis

Learn more at [mgx.dev](https://mgx.dev) and the [company site](https://www.deepwisdom.ai)

Pricing/trial details are not clearly published; status unknown

How It Works

Role-based agents mirror a software company: PM, Architect, Project Manager, Engineer

SOPs govern agent collaboration and handoffs

Model-agnostic setup via API keys and config; supports local and hosted LLMs

Outputs include PRDs, design specs, tasks, and code from a single-line requirement

Explore the architecture and flows in the [Docs Introduction](https://docs.deepwisdom.ai/main/en/guide/get_started/introduction.html).

Key Capabilities

PRD and planning automation with structured, repeatable outputs

Architecture and API spec drafting

Repo scaffolding and initial code generation

Multi-agent experiments for data analysis and reporting

Local model support via integrations (e.g., Ollama, DeepSeek) as shown in the [IBM tutorial](https://www.ibm.com/think/tutorials/multi-agent-prd-ai-automation-metagpt-ollama-deepseek)

Who It’s For

Individual developers seeking fast PRDs, scaffolds, and prototypes

Product managers needing structured planning docs from brief inputs

Small teams piloting multi-agent workflows with local or hosted models

Teams adopting SOP-based orchestration for repeatable software tasks

Common Use Cases

PRD generation and competitive analysis from a one-line requirement

Architecture drafts, API specs, and design documentation

Repo scaffolding and starter code for greenfield projects

Multi-agent data analysis and internal reporting

PRD automation with local models using Ollama and DeepSeek

Integrations and Ecosystem

Model-agnostic configuration via `config2.yaml` and API keys

Demonstrated with Ollama and DeepSeek for local/cost-effective runs

Typical developer flow aligns with Git/GitHub and Python CLI

Getting Started (Open Source)

Install: `pip install metagpt`

Try it: `metagpt "your idea"`

Configure: `metagpt --init-config`, then set model/API keys in `config2.yaml`

Reference the [Quickstart](https://docs.deepwisdom.ai/main/en/guide/get_started/quickstart.html) and [Setup](https://docs.deepwisdom.ai/main/en/guide/get_started/setup.html) for details.

Market Signals and Sentiment

Pros

Strong at generating structured artifacts (PRDs, diagrams, flow charts) from short prompts

Clear “AI team” mental model that matches PM/engineering workflows

Active open-source framework with community attention

Quick CLI setup and sensible defaults for rapid trials

Demonstrated pairing with local LLM stacks for PRD automation

Cons

Code quality can be inconsistent without oversight

Concerns about hype and reliability on complex builds

Research credibility questioned in discussions about reported baselines

Mixed outcomes reported for MGX on real projects; results vary by scope/expectations

Practical Considerations

Treat outputs as draftable scaffolds; plan human review for code and architecture

For sensitive or cost-constrained workloads, consider local models via Ollama/DeepSeek

Establish SOP checkpoints to improve consistency and reduce error propagation

Clarify MGX pricing/trial status directly with the team through [mgx.dev](https://mgx.dev) or [LinkedIn](https://www.linkedin.com/company/metagpt)

Resources

Documentation: [Introduction](https://docs.deepwisdom.ai/main/en/guide/get_started/introduction.html) • [Quickstart](https://docs.deepwisdom.ai/main/en/guide/get_started/quickstart.html) • [Setup](https://docs.deepwisdom.ai/main/en/guide/get_started/setup.html) • [Tutorials](https://docs.deepwisdom.ai/main/en/guide/tutorials/multi_agent_101.html)

Code: [MetaGPT on GitHub](https://github.com/FoundationAgents/MetaGPT)

Company: [DeepWisdom.ai](https://www.deepwisdom.ai) • [MGX](https://mgx.dev) • [LinkedIn](https://www.linkedin.com/company/metagpt)

Guide: [IBM tutorial on PRD automation with MetaGPT, Ollama, and DeepSeek](https://www.ibm.com/think/tutorials/multi-agent-prd-ai-automation-metagpt-ollama-deepseek)

Community Sentiment: [r/ChatGPTPro](https://www.reddit.com/r/ChatGPTPro/comments/168yjo6/metagpt_the_next_evolution_or_just_more_hype/) • [r/ProductManagement](https://www.reddit.com/r/ProductManagement/comments/163vekc/thoughts_on_metagpt/) • [r/MachineLearning](https://www.reddit.com/r/MachineLearning/comments/1axbm0f/d_metagpt_grossly_misreported_baseline_numbers/) • [r/foundationagents](https://www.reddit.com/r/foundationagents/comments/1n6eq0t/testing_metagpt_x_for_my_side_project_worth_it_or/) • [r/github](https://www.reddit.com/r/github/comments/14q5h0j/metagpt_make_gpt_form_a_software_company_to/)

Related Companies

AgentGPT

AgentGPT is an open‑source, browser‑run tool from Reworkd that lets you name an agent, set a goal, and have it autonomously plan, research, and execute tasks in iterative loops. It’s designed for fast experimentation and demos, with ready‑made templates for research, branding, and trip planning—no engineering setup required.

BabyAGI

BabyAGI is pioneering the future of autonomous AI through an experimental framework designed for self-building agents. Born from the insight that the most effective path to general autonomous agents is radical simplicity, BabyAGI focuses on creating the minimal viable system capable of building and evolving itself. At its core is functionz, an innovative function framework that revolutionizes how autonomous agents manage their capabilities. This database-driven system stores, manages, and executes functions through an intelligent graph-based architecture that tracks imports, dependencies, and authentication—all with automatic loading and comprehensive logging. BabyAGI provides developers with an intuitive dashboard for seamless function management, real-time updates, and detailed log analysis, making autonomous agent development accessible and transparent. By embracing a self-building philosophy, BabyAGI represents a fundamentally new approach to creating AI systems that can adapt, grow, and improve autonomously.

CrewAI

CrewAI is at the forefront of Agentic AI with its open source, multi-agent framework and cloud platform for building, managing and scaling agentic workflows across the entire organization.

Flowise AI

Flowise is an open source drag & drop tool to build your customized LLM flow. We provide a visual interface to let you build backends for LLM apps used for QnA, summarization and analysis on your documents.

LangChain

LangChain provides the agent engineering platform and open source frameworks developers need to ship reliable agents fast.

LlamaIndex

LlamaIndex empowers developers to build agents that extract insights and take action on complex enterprise documents. It combines industry-leading document parsing and extraction with a trusted framework for building intelligent agents that reason over documents, adapt to business logic, and scale to production. LlamaIndex is loved by developers and trusted by enterprises. Its open source framework is downloaded more than 4M+ every month and has processed more than 200 million documents on LlamaCloud.