Mastra vs Scrapegraph-ai
Side-by-side comparison of two AI agent tools
Short answer
- Scrapegraph-ai has had no commit in 6 months; Mastra is actively maintained (4,109 commits in the last 90 days).
- Scrapegraph-ai is growing faster: +1,928 GitHub stars in the last 30 days vs +968 for Mastra.
- Pick Mastra for: from the team behind Gatsby, Mastra is a framework for building AI-powered applications and agents. Pick Scrapegraph-ai for: python scraper based on AI.
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.
Scrapegraph-aiopen-source
Python scraper based on AI
Metrics
| Mastra | Scrapegraph-ai | |
|---|---|---|
| Stars | 28.5k | 23.1k |
| Star velocity /mo | 968.3684210526316 | 1.9k |
| Commits (90d) | 4.1k | — |
| Releases (6m) | 10 | 10 |
| Downloads (30d, npm + PyPI) | 3.1M | — |
| Overall score | 0.8983723604743185 | 0.6290716468546114 |
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
- +基于 LLM 的智能解析,无需手写复杂的选择器规则
- +支持多种数据格式(网站、XML、HTML、JSON、Markdown),具有广泛的适用性
- +自然语言交互方式,大幅降低使用门槛,提高开发效率
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
- -依赖大语言模型,可能产生额外的 API 调用成本
- -AI 推理过程可能比传统爬虫速度较慢
- -对于大规模、高频率的数据抓取场景,性能可能不如专门优化的传统爬虫
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
- •电商网站产品信息批量提取和价格监控
- •新闻文章和博客内容的自动化采集和分析
- •企业数据迁移中多种格式文档的结构化数据提取
FAQ
- Which is more popular, Mastra or Scrapegraph-ai?
- Mastra has more GitHub stars (28,525 vs 23,140).
- Should I use Mastra or Scrapegraph-ai?
- Compare their capabilities, limitations and "best for" notes above. Trying each on a small task is the fastest way to decide.