MetaGPT vs SWE-agent

Side-by-side comparison of two AI agent tools

Short answer

  • MetaGPT has had no commit in 8 months; SWE-agent is actively maintained (6 commits in the last 90 days).
  • MetaGPT is growing faster: +696 GitHub stars in the last 30 days vs +254 for SWE-agent.
  • Pick MetaGPT for: the Multi-Agent Framework: First AI Software Company, Towards Natural Language Programming. Pick SWE-agent for: sWE-agent takes a GitHub issue and tries to automatically fix it, using your LM of choice.

From GitHub data refreshed daily.

MetaGPTopen-source

🌟 The Multi-Agent Framework: First AI Software Company, Towards Natural Language Programming

SWE-agentopen-source

SWE-agent takes a GitHub issue and tries to automatically fix it, using your LM of choice. It can also be employed for offensive cybersecurity or competitive coding challenges. [NeurIPS 2024]

Metrics

MetaGPTSWE-agent
Stars70.7k20.5k
Star velocity /mo695.5263157894738254.3684210526316
Commits (90d)06
Releases (6m)00
Overall score0.3777391480437980.4088976488846652

Pros

  • +完整的软件开发流程自动化，从需求到代码生成覆盖整个开发生命周期
  • +基于角色的多智能体架构，模拟真实软件公司的协作模式
  • +强大的社区支持和学术认可，GitHub获得66000+星标，相关论文在ICLR 2025获得口头报告资格
  • +在SWE-bench基准测试中达到开源项目的最先进性能水平
  • +支持多种主流大语言模型（GPT-4o、Claude Sonnet 4等），配置灵活
  • +专为研究设计，架构简单且文档完善，易于定制和扩展

Cons

  • -对Python版本有严格限制，要求3.9及以上但低于3.12版本
  • -多智能体系统的复杂性可能导致设置和调试困难
  • -运行多个LLM角色可能消耗大量计算资源和API调用成本
  • -开发重心已转移到mini-swe-agent项目，原项目维护可能受到影响
  • -主要面向研究用途，生产环境的稳定性和可靠性可能不如商业解决方案

Use Cases

  • •将一行业务需求自动转换为完整的软件规格说明和技术文档
  • •自动化软件架构设计，生成数据结构、API接口和系统架构图
  • •端到端软件开发流程自动化，适用于快速原型开发和MVP构建
  • •自动修复GitHub仓库中的代码问题和bug
  • •网络安全领域的漏洞发现和渗透测试
  • •竞赛编程和算法挑战的自动化解决
View MetaGPT DetailsView SWE-agent Details

FAQ

Which is more popular, MetaGPT or SWE-agent?
MetaGPT has more GitHub stars (70,725 vs 20,475).
Which is more actively developed, MetaGPT or SWE-agent?
SWE-agent had more commits in the last 90 days (6 vs 0).
Should I use MetaGPT or SWE-agent?
Compare their capabilities, limitations and "best for" notes above. Both are open source, so trying each on a small task is the fastest way to decide.