TypeScript-native AI agent framework for building agents with tools, workflows, RAG, and memory — designed for the JavaScript/TypeScript ecosystem.
A TypeScript toolkit for building AI agents and workflows that connect to your existing business tools through ready-made integrations.
Mastra is an open-source TypeScript-native framework for building AI agents, designed specifically for the JavaScript/TypeScript ecosystem. While most AI agent frameworks are Python-first, Mastra provides first-class TypeScript support with full type safety, making it the go-to choice for teams building agents in Node.js, Next.js, and other JavaScript environments.
The framework provides a comprehensive set of primitives for agent development: LLM integration with multiple providers (OpenAI, Anthropic, Google), tool definition with typed schemas, workflow orchestration with step-based pipelines, RAG with vector store integration, and persistent memory management. All of these are designed with TypeScript's type system, providing autocompletion, compile-time checks, and excellent developer experience.
Mastra's workflow engine supports sequential, parallel, and conditional execution patterns with built-in error handling and retries. Workflows can include human-in-the-loop steps where execution pauses for user input. The framework also provides syncing integrations with third-party APIs, making it easy to give agents access to external services.
For RAG applications, Mastra includes document processing, chunking, embedding, and vector store integration with Pinecone, pgvector, and other providers. The memory system supports both short-term conversation context and long-term persistent memory with configurable backends.
Mastra includes a development dashboard for testing agents interactively, inspecting tool calls, and debugging workflows. The framework deploys naturally to Vercel, Cloudflare Workers, AWS Lambda, and any Node.js hosting environment. With growing adoption in the TypeScript community, Mastra fills an important gap in the agent framework landscape.
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Built from the ground up for TypeScript with full type safety, autocompletion, and compile-time checks — not a Python port.
Use Case:
Define agent tools with Zod schemas for automatic validation, type inference, and LLM function calling schema generation.
Use Case:
Step-based workflow engine with sequential, parallel, and conditional patterns, including human-in-the-loop pause and resume.
Use Case:
Document processing, chunking, embedding, and vector store integration for building knowledge-grounded agents.
Use Case:
Configurable memory backends for conversation context and long-term agent memory that persists across sessions.
Use Case:
Interactive UI for testing agents, inspecting tool calls, debugging workflows, and monitoring agent behavior during development.
Use Case:
Free
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View Pricing Options →Building AI agents in TypeScript/JavaScript projects
Full-stack web applications with embedded AI agents
Serverless agent deployments on Vercel or Cloudflare
Teams with TypeScript expertise wanting type-safe agent development
We believe in transparent reviews. Here's what Mastra doesn't handle well:
Mastra is TypeScript-native with better type safety and developer experience. LangChain.js is a port from Python that doesn't always feel natural in TypeScript. Mastra's workflow and memory systems are also more integrated.
Yes. Mastra agents deploy naturally to Vercel, Cloudflare Workers, AWS Lambda, and any environment that runs Node.js.
Yes. Mastra supports streaming responses from LLM providers, enabling real-time agent interactions in web applications.
Mastra integrates with Pinecone, pgvector, and other vector stores for RAG applications, with more integrations being added regularly.
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