Mastra at a glance

Starting price: $250/mo (Platform Teams)
Free plan: Yes
Platforms: Web, Desktop, API

What is Mastra?

Mastra is an Apache 2.0 licensed TypeScript framework for building AI agents and agentic workflows, created by the team behind Gatsby. It provides the pieces engineers otherwise assemble themselves: agent primitives, persistent memory, retrieval-augmented generation, workflow orchestration, evaluation harnesses and MCP support, with a local development playground for testing behaviour before deployment.

Position it correctly against the no-code tools in this category. Mastra is a developer framework, not a visual builder, so it assumes TypeScript fluency and offers control rather than speed to first automation; teams wanting drag-and-drop should look elsewhere entirely. The framework itself is free to self-host under a permissive licence, with a separate managed cloud platform for deployment and observability priced independently, so evaluate the two decisions separately.

Key Features

TypeScript NativeApache 2.0 LicenseAgent PrimitivesDurable WorkflowsObservational MemoryRAG PipelinesMCP SupportAgent EvalsGuardrailsTracing and ObservabilityMastra StudioAgent BuilderModel GatewayLocal Dev PlaygroundVercel DeployerCloudflare DeployerNetlify DeployerSelf-Hosted Option

Integrations

Other

OpenAIAnthropicGoogle Gemini

Development

VercelCloudflareNetlifyNext.jsGitHub

Database

PostgresPinecone

How to Use Mastra

1Run npm create mastra to scaffold a project

2Define an agent with a model, tools, memory and instructions

3Compose a durable workflow with typed control flow

4Test locally in the dev playground and inspect traces

5Add evals and guardrails before production

6Deploy to Vercel, Cloudflare, Netlify or your own Node infrastructure

7Optionally connect Mastra Platform for hosted observability and Studio

Who is Mastra for?

✅ Best For

TypeScript engineering teams shipping AI agents inside an existing Next.js, React or Node application rather than adopting a separate no-code platform
Developers who want agents, memory, RAG, workflows and evals from one coherent framework instead of assembling four libraries that were never designed together
Teams that need agent output quality measured, since built-in model-graded, rule-based and statistical evals let you track regression over time
Organisations with data residency requirements, because the framework is fully self-hostable and enterprise deployments keep traces and prompts inside your own VPC

❌ Not For

Non-technical users entirely, since Mastra is a code framework with no visual builder for the core workflow authoring experience
Python-first teams, as Mastra is purpose-built for TypeScript and a Python shop is better served by frameworks in its own ecosystem
Teams wanting prebuilt SaaS connectors out of the box, because Mastra gives you primitives and tools rather than a library of thousands of app integrations
Anyone needing a finished product today, as building a reliable production agent is engineering work regardless of how good the framework is

Reviews

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Pricing

Is Mastra free? Yes, there is a free plan. Paid plans start at $250/mo (Platform Teams).

Framework$0

✓Apache 2.0 licensed
✓self-host anywhere
✓agents
✓workflows
✓memory and evals included

Platform Starter$0

✓100K observability events
✓24 CPU hours
✓15-day retention
✓unlimited users and projects

Platform Teams$250/mo

✓1M observability events
✓250 CPU hours
✓6-month retention
✓multiple teams
✓SSO and SOC 2 docs

Platform EnterpriseCustom

✓Custom volume and retention
✓RBAC
✓audit logs
✓uptime SLAs
✓dedicated support engineer

Self-Hosted EnterpriseCustom

✓Flat annual fee
✓enterprise controls
✓data stays in your VPC
✓no per-trace or per-seat metering

Prompts to Try

Scaffold a Mastra agent that answers product questions using a RAG pipeline over our docs

Build a durable workflow that chains three agents with typed inputs and outputs

Add an eval suite that scores agent responses for factual accuracy over time

Deploy this Mastra agent as a standalone Hono server on Cloudflare Workers

Use Cases

Tobias is a staff engineer at a developer tools company who shipped an in-product AI assistant using Mastra inside their existing Next.js app, avoiding the separate service and deployment pipeline a Python framework would have required.

Yuki leads AI engineering at a fintech and used Mastra's eval suite to catch a regression where a model update dropped answer accuracy by 11 percent, before it reached a single customer.

Ravi builds internal tooling at a logistics firm and composed a durable multi-step workflow where one agent extracts shipment data, another validates it and a third writes to their ERP, with typed contracts between each step.

Elena is a solo technical founder who used Mastra's observational memory so her support agent remembers context across sessions, which turned a demo that impressed nobody into one that closed her first three customers.

Anders runs platform engineering at an enterprise with strict data rules and deployed self-hosted Mastra so no traces, prompts or outputs leave their VPC, which cleared a security review that had blocked two previous vendors.