LangGraph vs Mastra

Side-by-side comparison of two AI agent tools

Short answer

  • LangGraph is growing faster: +2,365 GitHub stars in the last 30 days vs +968 for Mastra.
  • Pick LangGraph for: build resilient language agents as graphs. Pick Mastra for: from the team behind Gatsby, Mastra is a framework for building AI-powered applications and agents.

From GitHub data refreshed daily.

LangGraphopen-source

Build resilient language agents as graphs.

Mastrafree

From the team behind Gatsby, Mastra is a framework for building AI-powered applications and agents with a modern TypeScript stack.

Metrics

LangGraphMastra
Stars42.7k28.5k
Star velocity /mo2.4k968.3684210526316
Commits (90d)1324.1k
Releases (6m)1010
Downloads (30d, npm + PyPI)43.7M3.1M
Overall score0.80913195306925360.8983723604743185

Pros

  • +Durable execution ensures agents automatically resume from exactly where they left off after failures or interruptions
  • +Comprehensive memory system with both short-term working memory for ongoing reasoning and long-term persistent memory across sessions
  • +Seamless human-in-the-loop capabilities allow for inspection and modification of agent state at any point during execution
  • +统一的多提供商接口支持 40+ AI 模型提供商,避免供应商锁定
  • +完整的 AI 应用工具链包括代理、工作流、人机交互和上下文管理
  • +TypeScript 原生支持和现代技术栈集成,开发体验优秀

Cons

  • -Low-level framework requires more technical expertise and setup compared to high-level agent builders
  • -Graph-based agent design paradigm may have a steeper learning curve for developers new to agent orchestration
  • -Production deployment complexity may be overkill for simple chatbot or single-turn use cases
  • -作为相对较新的框架,生态系统和社区资源可能有限
  • -多功能集成可能带来学习曲线,需要时间掌握各个组件
  • -文档和最佳实践可能还在完善中,缺少大规模生产案例

Use Cases

  • •Long-running autonomous agents that need to persist through system failures and operate over days or weeks
  • •Complex multi-step workflows requiring human oversight, approval, or intervention at specific decision points
  • •Stateful agents that must maintain context and memory across multiple sessions and interactions
  • •构建需要多个 AI 模型协作的复杂智能代理系统
  • •开发需要人机交互审批流程的自动化工作流应用
  • •快速原型验证 AI 产品概念并扩展到生产环境

FAQ

Which is more popular, LangGraph or Mastra?
LangGraph has more GitHub stars (42,656 vs 28,525).
Which is more actively developed, LangGraph or Mastra?
Mastra had more commits in the last 90 days (4,109 vs 132).
Should I use LangGraph or Mastra?
Compare their capabilities, limitations and "best for" notes above. Trying each on a small task is the fastest way to decide.