Mastra 1.0
Hi HN, we’re Sam, Shane, and Abhi, and we’re building Mastra (https://mastra.ai), an open-source JavaScript SDK for building agents on top of Vercel’s AI SDK. You can start a Mastra project with `npm create mastra` and create workflow graphs that can suspend/resume, build a RAG pipeline and write evals, give agents memory, create multi-agent workflows, and view it all in a local playground. Previously, we built Gatsby, the open-source React web framework. Later, we worked on an AI-powered CRM but it felt like we were having to roll all the AI bits (agentic workflows, evals,…
Mastra 1.0 launched on January 21, 2026 with 451 votes, #27 of 14,585 launches that month and more than 99% of that year's launches.
In plain words
Mastra is a TypeScript framework for building AI-powered applications and agents. It includes tools for creating workflows, managing memory, streaming responses, running evaluations, and tracing execution. The platform provides Studio, an interactive interface for development and testing. Developers can get started with a single command to scaffold a new project. Built by the team behind Gatsby, Mastra targets developers looking to construct production-ready AI applications.
written from the facts on this page · September 2026
From the sources
From the team behind Gatsby, Mastra is a framework for building AI-powered apps and agents with workflows, memory, streaming, evals, tracing, and Studio, an interactive UI for dev and testing. Start building: npm create mastra@latest
Mastra is the modern TypeScript framework for AI-powered applications and agents. - mastra-ai/mastra
In the maker’s words, at launch
Hi HN, we’re Sam, Shane, and Abhi, and we’re building Mastra (https://mastra.ai), an open-source JavaScript SDK for building agents on top of Vercel’s AI SDK. You can start a Mastra project with `npm create mastra` and create workflow graphs that can suspend/resume, build a RAG pipeline and write…
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Mastra FactoryAug 2026 · mastra.ai · ▲536We wanted to build a course for new Mastra devs to get started quickly. However, we knew videos would go out of date and be more difficult to maintain. We decided to launch our "course" as an MCP server. This way your coding agent actually teaches the course content to you and can help you write the code. We think this is a really interactive way to learn. Using an editor with MCP support (such as Cursor, Windsurf, or VSCode), your code agent will call the appropriate MCP tools which will return context for the agent. This context tries to instruct the agent that it should be teaching you…
Locofy.ai2022 · locofy.ai · ▲720Hey there, I am Honey - Co-founder at Locofy. We, along with other makers, have been building Locofy.ai to help massively accelerate the builders - the designers, developers, product managers & founders, and we're excited to share it today with the HN Community. Locofy.ai simply converts designs into production-ready frontend code for web and mobile apps. It adapts to your preferred design tools, tech stack, and workflows with ease and lets you launch upto 4x faster, while letting designers design the way they want and giving high-quality responsive code that developers love. With this…


Nous – Open-Source Agent Framework with Autonomous, SWE Agents, WebUI2024 · github.com · ▲155Hello HN! The day has finally come to stop adding features and start sharing what I've been building the last 5-6 months. It's a bit of CrewAI, OpenDevon, LangFuse/Cloud all in one, providing devs who prefer TypeScript an integrated framework thats provides a lot out of the box to start experimenting and building agents with. It started after peeking at the LangChain docs a few times and never liking the example code. I began experimenting with automating a simple Jira request from the engineering team to add an index to one of our Google Spanner databases (for context I'm the…
Principles of Building AI Agents book [pdf]2025 · github.com · ▲5Hi, I’m Sam, the cofounder/CEO of Mastra, the Typescript agent framework. I wrote a book on building agents and wanted to share it with HN. The book is called Principles of Building AI Agents. Right now it has 34 chapters and 148 pages covering LLMs, prompting, agents, workflows, RAG, evals, multi-agent, tracing, deployment, MCP, tool use, and a few other topics. The backstory here is that last October when we started working on Mastra we knew very little about AI engineering, and had to learn as we were building. In January, we started going to local AI meetups. We met a lot of people…
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