
Mastra is an open-source TypeScript framework for building AI agents and AI-powered apps. It packages typed agents, graph workflows, memory, MCP support, and observability for JavaScript teams that want agent logic inside an existing app stack instead of a separate Python service.
Mastra treats agent development as a TypeScript app problem. Agents, workflows, memory, server endpoints, and observability can live beside React, Next.js, Node.js, Hono, Express, Fastify, or standalone server code. The graph workflow engine handles multi-step processes, pauses, branches, and parallel work, while MCP support exposes agents, tools, and resources to other systems.
Developers define an agent with instructions, a model, tools, and runtime behavior, then connect it to app flows. Mastra supports internal Slack-style agents, customer-facing task agents, and AI SREs. Memory combines message history with retrieval and persistent state, while observability covers evals, metrics, datasets, traces, token usage, and guardrails.
Deployment options include any Node.js-compatible environment, built-in deployers for Vercel, Netlify, and Cloudflare, a standalone Hono server, or existing web frameworks.
Mastra publishes customer examples rather than review-site scores. Marsh uses LenAI agentic search powered by Mastra, and MongoDB uses Mastra agents for CI logs. The tradeoff is audience fit: non-technical teams need developers, not just a visual builder.
Starter covers prototypes. Teams and Enterprise add retention, SSO, compliance docs, and production support.
Mastra is used to build TypeScript AI agents, workflows, MCP servers, memory systems, evals, and observability for AI apps.
Yes. Mastra has an Apache 2.0 open-source framework and a $0/month Starter Platform plan with metered overages.
Mastra was founded by Sam Bhagwat, Abhi Aiyer, and Shane Thomas, the team behind Gatsby.js.
Teams adds SSO and SOC 2 docs. Enterprise adds RBAC, audit logs, SLAs, and self-hosted VPC deployment options.
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