Code Lib / 代码库
更新于 a month ago

mastra

Mmastra-ai
20.4k
mastra-ai/mastra
84
Agent 评分

💡 摘要

Mastra 是一个用于构建、编排和部署生产就绪的 AI 智能体与工作流的 TypeScript 框架。

🎯 适合人群

构建 AI 功能的全栈 TypeScript 开发者为 AI 应用制作原型的产研团队需要可扩展智能体编排的后端工程师寻求结构化开发框架的 AI 研究员/工程师

🤖 AI 吐槽:这是 AI 智能体的瑞士军刀,但你需要一本说明书才能搞清楚哪片刀片是用来切 LLM 的,哪片是用来撬开顽固的工作流的。

安全分析中风险

风险包括任意工具/智能体执行(通过 MCP 服务器或自定义工具)、依赖供应链(40+ 模型提供商)以及通过存储/上下文导致的数据暴露。缓解措施:实施严格的输入验证,审计第三方工具权限,并对存储中的敏感数据进行加密。

Mastra

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Mastra is a framework for building AI-powered applications and agents with a modern TypeScript stack.

It includes everything you need to go from early prototypes to production-ready applications. Mastra integrates with frontend and backend frameworks like React, Next.js, and Node, or you can deploy it anywhere as a standalone server. It's the easiest way to build, tune, and scale reliable AI products.

Why Mastra?

Purpose-built for TypeScript and designed around established AI patterns, Mastra gives you everything you need to build great AI applications out-of-the-box.

Some highlights include:

  • Model routing - Connect to 40+ providers through one standard interface. Use models from OpenAI, Anthropic, Gemini, and more.

  • Agents - Build autonomous agents that use LLMs and tools to solve open-ended tasks. Agents reason about goals, decide which tools to use, and iterate internally until the model emits a final answer or an optional stopping condition is met.

  • Workflows - When you need explicit control over execution, use Mastra's graph-based workflow engine to orchestrate complex multi-step processes. Mastra workflows use an intuitive syntax for control flow (.then(), .branch(), .parallel()).

  • Human-in-the-loop - Suspend an agent or workflow and await user input or approval before resuming. Mastra uses storage to remember execution state, so you can pause indefinitely and resume where you left off.

  • Context management - Give your agents the right context at the right time. Provide conversation history, retrieve data from your sources (APIs, databases, files), and add human-like working and semantic memory so your agents behave coherently.

  • Integrations - Bundle agents and workflows into existing React, Next.js, or Node.js apps, or ship them as standalone endpoints. When building UIs, integrate with agentic libraries like Vercel's AI SDK UI and CopilotKit to bring your AI assistant to life on the web.

  • MCP servers - Author Model Context Protocol servers, exposing agents, tools, and other structured resources via the MCP interface. These can then be accessed by any system or agent that supports the protocol.

  • Production essentials - Shipping reliable agents takes ongoing insight, evaluation, and iteration. With built-in evals and observability, Mastra gives you the tools to observe, measure, and refine continuously.

Get started

The recommended way to get started with Mastra is by running the command below:

npm create mastra@latest

Follow the Installation guide for step-by-step setup with the CLI or a manual install.

If you're new to AI agents, check out our templates, course, and YouTube videos to start building with Mastra today.

Documentation

Visit our official documentation.

MCP Servers

Learn how to make your IDE a Mastra expert by following the @mastra/mcp-docs-server guide.

Contributing

Looking to contribute? All types of help are appreciated, from coding to testing and feature specification.

If you are a developer and would like to contribute with code, please open an issue to discuss before opening a Pull Request.

Information about the project setup can be found in the development documentation

Support

We have an open community Discord. Come and say hello and let us know if you have any questions or need any help getting things running.

It's also super helpful if you leave the project a star here at the top of the page

Security

We are committed to maintaining the security of this repo and of Mastra as a whole. If you discover a security finding we ask you to please responsibly disclose this to us at security@mastra.ai and we will get back to you.

五维分析
清晰度9/10
创新性7/10
实用性9/10
完整性8/10
可维护性9/10
优缺点分析

优点

  • 为 40+ AI 模型提供商提供统一接口
  • 生产就绪功能:评估、可观测性、存储
  • 与现代 Web 技术栈(React、Next.js)深度集成
  • 同时支持自主智能体和显式工作流编排

缺点

  • 主要专注于 TypeScript,对其他语言支持较弱
  • 对于简单的 AI 任务可能显得复杂
  • 相比成熟的替代方案,生态系统较新
  • 丰富的功能集需要学习成本才能充分利用

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免责声明:本内容来源于 GitHub 开源项目,仅供展示和评分分析使用。

版权归原作者所有 mastra-ai.