Mastra
Mastra is an open-source TypeScript framework for AI agents and applications, developed since 2024. It bundles agents with instructions and tools, typed workflows with branching and retries, memory functions, plus tracing, metrics and evaluations.
Mastra is an open-source TypeScript framework for AI agents: agents with tools, typed workflows, memory and built-in traceability in one package.
Explanation
Mastra answers the question that arrives after the first prototype: how does an agent become part of a system? It separates responsibilities cleanly. An agent knows its mandate, tools and model. A workflow describes steps that must run reliably in order and with retries. Memory decides what an agent keeps across sessions. And because tracing and evaluations are built in, quality can be measured rather than asserted. The framework is young: APIs still move, and there is no hosted infrastructure of its own — storage and operations are on you. A publicly documented data processing agreement from the vendor could not be verified, which needs clarifying where personal data is involved.
Marketing Relevance
For teams already working in TypeScript, the switch to Python disappears — an underrated factor, because maintenance stays where the website lives. For accountable owners it matters most that evaluations and logs are part of the framework: agent performance can then be accepted with numbers rather than impressions.
Example
An editorial agent researches sources, drafts a piece and submits it for approval. The workflow fixes the order, retries failed steps and logs every tool call with its cost for later evaluation.
Common Pitfalls
As a young framework, Mastra changes APIs more often than production teams like — pin versions and plan upgrades. And because no hosted operation is included, responsibility for storage, backups and data sovereignty stays entirely in-house.
Origin & History
Mastra has been developed since 2024 by a team with Gatsby-era experience and published openly on GitHub. It grew quickly into one of the better-known TypeScript frameworks for agents, extending workflows, memory and evaluations with controller layers for multi-step agents.
Further Resources
Marketing Use Cases
Multi-step marketing workflows with an approval step.
Agents with memory across sessions, for instance in customer service.
Evaluations as acceptance criteria for agent quality.
Integration of internal tools through typed interfaces.
Frequently Asked Questions
Mastra or LangGraph?
LangGraph is more established in the Python world and models flows as a graph. Mastra is TypeScript-native and brings workflows, memory and evaluations together. The choice usually follows the team's primary language.
Can I self-host Mastra?
Yes, that is the normal case. There is no mandatory hosted platform; you provide storage and runtime, which eases data sovereignty and increases operational effort.
Is the framework production-ready?
For bounded, explicitly accepted use cases yes, with pinned versions and your own monitoring. If you need stability over years, plan for the rate of API change.
Related Services
Go deeper: Agentic AI Hub · Model comparison 2026