Mastra — TypeScript AI agent framework with observability and deployment. Best for TypeScript developers building AI agents and AI-powered applications, Projects requiring multi-step workflows with human approval steps, Teams that need built-in observability and evaluation for agent performance. Free to start; paid plans from $2/mo.
TypeScript developers building AI agents and AI-powered applicationsProjects requiring multi-step workflows with human approval stepsTeams that need built-in observability and evaluation for agent performanceStartups wanting a modular, open-source framework with model-agnostic APIDeploying agent endpoints alongside existing Next.js or Node.js apps
Not ideal for
Teams preferring Python-based AI ecosystems like LangChain or LlamaIndexProjects needing extensive pre-built integrations beyond the built-in providersNon-developers seeking a no-code agent builder (Mastra is code-first)Scenarios requiring a fully managed platform without self-hosting optionsUse cases demanding real-time inference at ultra-low latency (not optimized for streaming)
A solid choice for TypeScript developers who want to build AI agents without leaving the JS ecosystem. It's not as mature as Python alternatives but offers tight integration with modern web frameworks.
Mastra is a refreshingly pragmatic TypeScript-first framework for AI agents. If you're a JavaScript/TypeScript developer looking to build agentic applications without switching to Python, Mastra provides a clean, modular set of primitives: agents, workflows, memory, and observability. The built-in support for 90+ models via a single API is a major time-saver, and the graph-based workflow engine with human-in-the-loop is rare in TS frameworks. However, the ecosystem is newer, so community templates and integrations are limited compared to LangChain. Deployment is straightforward with built-in support for Vercel, Netlify, and Cloudflare. The open-core model is fair: core Apache 2.0, enterprise features source-available. Consider Mastra if you're all-in on TypeScript and want to avoid Python dependency. Skip it if you need extensive pre-built tool integrations or if your team prefers Python's AI ecosystem. Real-world usage: expect to build more custom tooling, but the framework's architecture makes that manageable.
Skip Mastra if Skip Mastra if you need a Python-native AI framework, pre-built enterprise integrations, or a no-code agent builder.
Latest from Mastra
Updated today
Across the latest 9 updates: 7 feature updates and 2 launches.
How likely is Mastra to still be operational in 12 months? Based on 6 signals including funding, development activity, and platform risk.
funding runway
80
website health
90
github activity
50
category mortality
70
wrapper dependency
100
hyperscaler overlap
80
About Mastra
Mastra is an open-source TypeScript framework for building AI-powered applications and agents. It provides agents, workflows, memory, workspaces, and observability, enabling developers to go from idea to implementation. The framework is designed for TypeScript developers and integrates with frontend and backend frameworks like React, Next.js, and Node.js, or can be deployed standalone. Mastra supports 90+ AI model providers through a standard interface, includes a graph-based workflow engine with human-in-the-loop support, and offers built-in observability with traces, logs, and evaluation tools. It also includes a memory system for conversation history and context retrieval. Mastra's core framework is open source under Apache 2.0, with enterprise features available under a separate license.
Researching Mastra? Skip the guesswork.
Tell us what you want to build — we'll match the AI tools that fit your goal, budget & existing stack.
Key Features
TypeScript-first agent framework
Built-in observability with traces and logs
Graph-based workflow engine
Human-in-the-loop workflows
Memory system with retrieval
AI Gateway for model routing
Supports 90+ model providers
Open source under Apache 2.0
Evaluations with custom evals
Guardrails for prompt injection prevention
Deploy as standalone server or with Next.js, Express, Hono
Built-in deployers for Vercel, Netlify, Cloudflare
Real-world workflow fit
Concrete scenarios for the personas Mastra actually fits — and what changes day-one when you adopt it.
TypeScript developer prototyping a customer support agent
You run 'npm create mastra' to scaffold a project, define an agent with OpenAI, add a tool to query a database, and test it in Mastra Studio.
Outcome: You have a working agent you can chat with locally in under 10 minutes.
Team lead evaluating observability for production agents
You deploy an agent to Mastra Cloud, enable traces and logs, and set up a custom eval to monitor response quality.
Outcome: You get a dashboard with metrics, logs, and traces, plus alerts on eval failures.
Developer integrating a Slack bot using Mastra
You use the Channels feature to connect your agent to Slack, then deploy via the Mastra platform.
Outcome: Your agent is accessible in Slack, responding to messages with context persistence.
Newer project than Python incumbents — smaller community, fewer examples, shorter track record. Evals and observability are good but not as battle-tested as LangSmith. Cloud tier is newer and feature-scoped. Some advanced features (e.g., persistent server for 24/7 uptime) cost extra even on paid plans. Limited pre-built integrations for enterprise tools like Salesforce or SAP.
12-month cost
Project the real annual outlay, including the implied monthly cost when only an annual tier is published.
Annual total
Free
Over 12 months
Effective monthly
Free
Billed monthly
Vendor list price only. Add-on usage, seat overages, and contract minimums are surfaced under Hidden costs & gotchas.
Plans compared
For each published Mastra tier: who it actually fits, and what it adds vs. the previous tier. Cross-reference the cost calculator above for projected annual outlay.
Free (Open Source)
$0/mo (Apache 2.0)
Starter
$0/mo
Ideal for
Solo developer or small team wanting cloud-hosted observability with 100K events and 24 CPU hours.
What this tier adds
Adds cloud observability, studio, and memory gateway with limited events and retention.
Teams
$250/mo
Ideal for
Growing team needing more events, CPU time, 6-month retention, SSO, and SOC 2 docs.
What this tier adds
Scales to 1M events, 250 CPU hours, multiple teams, and longer data retention.
Enterprise
Custom
Ideal for
Large organization requiring custom volume, RBAC, audit logs, SLAs, and dedicated support.
What the public pricing page doesn't put in bold. Captured from pricing-page footnotes, contract terms, and recurring complaints.
•Overage on observability: $10/100K events after Starter's 100K
•CPU time overage: $0.35/hr after Starter's 24 hours
•Persistent Server (24/7 uptime) costs $100/project/month
•Memory gateway tokens: market rate + 5.5% markup
•Retrieval storage overage: $20/GB after included allotment
Where the pricing makes sense
The company stage and team size where Mastra's pricing actually pencils out — and where peers do it cheaper.
Mastra's open-source core is free. The cloud tiers (Starter $0, Teams $250/mo) target individual developers and growing teams; Enterprise custom pricing fits large orgs. Compared to LangSmith (usage-based, often pricier for heavy evals) or Vercel AI SDK (may require Vercel hosting), Mastra offers a self-hostable, more cost-predictable option for TypeScript teams. Persistent server add-ons and memory token markups can add up for high-volume use.
Setup time & first value
How long it actually takes to get something useful out of Mastra — broken out by persona, not the marketing-page minute.
For a TypeScript developer: first agent in under 5 minutes via 'npm create mastra'. Full project with tools, memory, and deployment: 1-2 hours using tutorials. Integrate with Next.js/Express: another 30 minutes. Complex multi-agent systems with A2A or browser support may take a day to configure.
Switching to or from Mastra
How to bring data in from common predecessors and how to get it back out — written for the switcher, not the buyer.
Migrating in
→From LangChain JS: Rewrite chains as Mastra workflows and use Mastra evals for testing.
→From Vercel AI SDK: Migrate stream handlers to Mastra agents with built-in observability.
→From OpenAI Assistants API: Wrap assistant logic in Mastra agents with custom tools and memory.
Migrating out
↗To LangChain: If Python ecosystem becomes necessary, rewrite agents in Python with LangChain.
↗To Vercel AI SDK: For simpler chat completions without agent orchestration.
↗To custom Express/Node: Extract agent logic and host as standalone API.
Recent material changes
Pricing, brand, ownership, or deprecation changes worth knowing before you commit. Most-recent first.
