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
| LangGraph | Mastra | |
|---|---|---|
| Stars | 42.7k | 28.5k |
| Star velocity /mo | 2.4k | 968.3684210526316 |
| Commits (90d) | 132 | 4.1k |
| Releases (6m) | 10 | 10 |
| Downloads (30d, npm + PyPI) | 43.7M | 3.1M |
| Overall score | 0.8091319530692536 | 0.8983723604743185 |
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.