Mastra
Mastra is a TypeScript-first framework for production AI agents and applications. It combines typed agents, graph workflows, memory, and built-in observability—metrics, logs, traces, and evals—plus model routing across 90+ providers, MCP servers, and straightforward Node-compatible deployments.
Overview
Start by defining a typed agent with instructions, a model, and tool functions. Compose a workflow that sequences steps, branches on conditions, and runs tasks in parallel. Attach memory retrieval for context. Instrument evals and traces, iterate in Studio, then deploy the agent server behind your app.
Capabilities
Mastra suits TypeScript teams shipping practical AI: product engineers embedding copilots into React and Next.js, platform groups building shared agent primitives, ops teams automating internal workflows through Slack, and data or research teams that need repeatable evals. It also fits teams standardizing multi-model access behind one API while keeping deep observability for reliability, performance, and cost control.
- Define typed agents with instructions, tools, and models in one file.
- Compose graph workflows using then, branch, and parallel control-flow primitives.
- Persist and retrieve memory from APIs, databases, and files for context.
- Trace tokens, logs, and tool calls with built-in evals and metrics.
- Deploy to Hono servers or cloud providers with minimal configuration changes.
Why teams choose Mastra
Use cases
Install with npm create mastra, which scaffolds a project with examples. Configure provider credentials, define your first Agent in TypeScript, and register tools. Add a workflow with .then(), .branch(), and .parallel() steps, run the dev server, and iterate in Studio while observing traces and evals. Deploy as a Hono server or integrate into Next.js or Node apps; optional deployers target Vercel, Netlify, and Cloudflare. Browse templates, books, and workshops to accelerate rollout, then promote agents to production with repeatable datasets and scoring.
Ship reliable TypeScript agents with explicit control, rich context, and production-grade telemetry.
Getting started
Mastra’s differentiator is unification: agents, workflows, memory, and observability designed together for TypeScript. Teams gain model portability via routing, operational trust through evals and traces, and pragmatic deployment via Node-compatible servers or turnkey cloud targets. Add MCP servers when interoperability matters and scale confidently from experiment to production.
Open the tool and review its core product experience.
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Use your own task to judge speed, quality, and fit.
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Mastra
Mastra is developed by a team focused on TypeScript AI engineering. They publish practical research, maintain open-source core libraries and enterprise extensions, and teach through books, workshops, and live sessions. The mission: help teams ship dependable, observable agentic systems from prototype to production.
Mastra is an open-source TypeScript framework for building AI-powered applications and agents. Developers define typed agents—instructions, models, tools, and runtime—in code, then orchestrate multi-step logic with a graph workflow engine supporting then, branch, and parallel paths. Mastra’s memory system blends conversation history with retrieval from APIs, databases, and files so agents stay grounded. Built-in observability surfaces metrics, logs, traces, datasets, and evals to measure changes before they reach production, with guardrails to sanitize inputs and outputs. Model routing connects to 90+ providers through one interface, letting teams swap OpenAI, Anthropic, Gemini and others without rewriting integrations. Apps run wherever Node.js runs: integrate with React or Next.js, ship a Hono-powered standalone server, or deploy via Vercel, Netlify, or Cloudflare. Mastra also supports authoring Model Context Protocol (MCP) servers to expose agents and tools over a standard interface. Core framework is Apache 2.0; enterprise features are source-available.
mastra.ai/
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