Mastra vs Opik
Side-by-side comparison of two AI agent tools
Short answer
- Mastra is growing faster: +969 GitHub stars in the last 30 days vs +607 for Opik.
- Pick Mastra for: from the team behind Gatsby, Mastra is a framework for building AI-powered applications and agents. Pick Opik for: debug, evaluate, and monitor your LLM applications, RAG systems, and agentic workflows with comprehensive.
From GitHub data refreshed daily.
Mastrafree
From the team behind Gatsby, Mastra is a framework for building AI-powered applications and agents with a modern TypeScript stack.
Opikopen-source
Debug, evaluate, and monitor your LLM applications, RAG systems, and agentic workflows with comprehensive tracing, automated evaluations, and production-ready dashboards.
Metrics
| Mastra | Opik | |
|---|---|---|
| Stars | 28.5k | 22.3k |
| Star velocity /mo | 969.2063492063492 | 606.8253968253969 |
| Commits (90d) | 4.0k | 1.0k |
| Releases (6m) | 10 | 10 |
| Overall score | 0.9035663973807672 | 0.8528137883272678 |
Pros
- +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
- +提供端到端的 AI 应用可观测性，包括详细的链路追踪和性能监控，帮助开发者快速定位问题
- +支持自动化评估和优化，能够自动改进提示词和工具配置，降低手动调优的工作量
- +完全开源且拥有活跃社区支持，提供灵活的部署选项和定制化能力
Cons
- -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
- -作为相对较新的工具，可能在某些企业级功能和集成方面还需要进一步完善
- -学习曲线可能较陡，需要开发者具备一定的 AI 应用开发和监控经验
Use Cases
- •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
- •RAG 聊天机器人的性能监控和优化，追踪检索质量和回答准确性
- •代码助手应用的链路分析，监控代码生成质量和响应时间
- •复杂智能体工作流的调试和评估，跟踪多步骤推理过程的执行效果
FAQ
- Which is more popular, Mastra or Opik?
- Mastra has more GitHub stars (28,498 vs 22,334).
- Which is more actively developed, Mastra or Opik?
- Mastra had more commits in the last 90 days (4,044 vs 1,044).
- Should I use Mastra or Opik?
- Compare their capabilities, limitations and "best for" notes above. Trying each on a small task is the fastest way to decide.