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Mastra icon

Mastra

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

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  • Online
  • Software as a Service (SaaS)
  • Typescript
  • JavaScript
  • npm
  • Mac
  • Windows
  • Linux
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Mastra information

  • Developed by

    US flagMastra
  • Licensing

    Open Source (Apache-2.0) and Free product.
  • Written in

  • Alternatives

    8 alternatives listed
  • Supported Languages

    • English

AlternativeTo Categories

AI Tools & ServicesDevelopment

GitHub repository

  •  19,869 Stars
  •  1,437 Forks
  •  304 Open Issues
  •   Updated  
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What is Mastra?

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.

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