Mastra: TypeScript-First AI Agent Framework

Mastra is a TypeScript-first framework for building AI agents and multi-step workflows. It provides the primitives most production agent systems need — agents, tools, memory, workflows, evals, and observability — in a single package rather than requiring you to stitch together separate libraries. The framework is Apache 2.0 licensed and runs on any Node.js-compatible environment including Bun, Deno, and Cloudflare Workers.

Mastra is used in production by Replit (Agent 3), SoftBank, PayPal, Marsh McLennan, and Sanity, among others.

• You are building agents in TypeScript/JavaScript and want a framework built for that ecosystem (not a Python-first framework with a JS port)
• You need multi-step workflows with suspend/resume, human-in-the-loop, and replay — not just single-call agents
• You want built-in observability, evals, and guardrails rather than wiring them separately
• You need supervisor-agent patterns for splitting work across specialized agents
• You want a visual development studio (Mastra Studio) for testing, tracing, and prompt refinement

• Unified primitives. Agents, tools, memory, workflows, evals, and observability in one framework. This eliminates the "stitch together five libraries" problem that plagues many JS agent setups.

• Type-safe workflows. Workflows are fully typed with sequential steps, parallel branches, conditional logic, and loops. You get compile-time safety on your control flow, which catches errors that Python agent frameworks only find at runtime.

• Human-in-the-loop is first-class. Any workflow step can suspend execution, hand control to a human, and resume when input arrives. State is persisted automatically — suspend today, resume next week.

• Rewind and replay. Workflow state is snapshotted at every step. You can time-travel back to any step with its original context to debug or replay from a specific point. This is genuinely useful for post-mortem analysis.

• Mastra Studio. A visual development environment where you run agents, trace execution, edit prompts, and create eval datasets. Non-technical team members (product managers, domain experts) can refine prompts and annotate traces without writing code. This is a real differentiator — most agent frameworks have no equivalent.

• Observational Memory. Mastra's memory system goes beyond simple message persistence. It learns about users across sessions and provides context-aware recall, reducing the need for manual context engineering.

• Model-agnostic. Connect to 1000+ models through a unified router. Switching providers is a configuration change, not a rewrite.

• MCP integration. Tools can be defined and shared via MCP, so your Mastra agents can use the same MCP servers as your Hermes, Claude, or other framework agents.

• Tool approval gates. Require human or external approval before any tool call executes — a governance pattern most frameworks leave to you to implement.

• TypeScript-only. If your team is Python-first, Mastra is the wrong choice. Pydantic AI, CrewAI, or LangChain serve Python teams better. Mastra does not have a Python SDK.

• Younger than LangChain. The ecosystem of community integrations, tutorials, and Stack Overflow answers is smaller. You will read official docs and source code more often than community posts.

• Enterprise features are custom-priced. The framework is free and open source. But RBAC, SSO, IAM integration, and enterprise observability are behind the Enterprise tier, which is "contact sales." No public per-seat or per-trace pricing for managed features.

• Studio is a development tool, not a production dashboard. Mastra Studio is excellent for development and testing. For production monitoring at scale, you may still want to integrate with an external observability platform (Langfuse, Datadog) for alerting and long-term retention.

• Workflow complexity has a learning curve. The type-safe workflow system is powerful but has its own mental model — steps, suspend/resume, snapshots. Teams used to simple chain-of-calls patterns will need time to learn it.

• No built-in code execution sandbox. If your agents need to write and execute code (like smolagents), Mastra does not provide this natively. You would integrate an external sandbox (E2B, Modal, Daytona).

• Free tier: Apache 2.0 licensed. Build and host agents anywhere. No feature gating on the core framework — agents, workflows, memory, tools, evals, and tracing are all free.
• Enterprise tier: Custom pricing. Adds RBAC, SSO, IAM, network policy integration, and guaranteed data stays in your VPC. One flat annual fee — no per-trace or per-seat metering.
• Mastra Cloud: Managed hosting for Mastra projects. Pricing not publicly listed as of August 2026.

Pricing verified against mastra.ai on 2026-08-12. Enterprise pricing requires a sales conversation.

TypeScript teams building production agent systems who want a single framework that covers agents, workflows, memory, evals, and observability without stitching together separate libraries. Particularly strong for teams that need human-in-the-loop workflows, multi-agent supervisor patterns, or a visual development studio for non-technical collaborators.

Not the right choice for Python-first teams, teams that need code-execution agents, or teams that want the largest community ecosystem (use LangChain for that).