Agent skill · Backend & API

mastra

Use this skill when working with Mastra - the TypeScript AI framework for building agents, workflows, tools, and AI-powered applications. Triggers on creating agents, defining workflows, configuring memory, RAG pipelines, MCP client/server setup, voice integration, evals/scorers, deployment, and Mastra CLI commands. Also triggers on "mastra dev", "mastra build", "mastra init", Mastra Studio, or any Mastra package imports.

majiayu000github.com/majiayu000GitHub ↗
claude-codeMIT
Install
npx skills add majiayu000/claude-skill-registry --skill mastra --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 2
SKILL.md size: 12 KB
Bundled scripts: none
Version: 0.1.0
Path: skills/ai-llm/mastra/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 534
Language: HTML

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

When this skill is activated, always start your first response with the 🧢 emoji. # Mastra Mastra is a TypeScript framework for building AI-powered applications. It provides a unified `Mastra()` constructor that wires together agents, workflows, tools, memory, RAG, MCP, voice, evals, and observability. Projects scaffold via `npm create mastra@latest` and run with `mastra dev` (dev server + Studio UI at `localhost:4111`). Built on Hono, deployable to Node.js 22+, Bun, Deno, Cloudflare, Vercel, Netlify, AWS, and Azure. --- ## When to use this skill Trigger this skill when the user: - Creates or configures a Mastra agent with tools, memory, or structured output - Defines workflows with steps, branching, loops, or parallel execution - Creates custom tools with `createTool` and Zod schemas - Sets up memory (message history, working memory, semantic recall) - Builds RAG pipelines (chunking, embeddings, vector stores) - Configures MCP clients to connect to external tool servers - Exposes Mastra agents/tools as an MCP server - Runs Mastra CLI commands (`mastra dev`, `mastra build`, `mastra init`) - Deploys a Mastra application to any cloud provider Do NOT trigger this skill for: - General

What's inside
Steps it walks through
  1. When to use this skill
  2. Setup & authentication
  3. Environment variables
  4. Installation
  5. Basic initialization
  6. Core concepts
  7. Common tasks
  8. Create an agent with tools
  9. Stream agent responses
  10. Define a workflow with steps
  11. Configure agent memory
  12. Connect to MCP servers
  13. Run CLI commands
  14. Error handling
Ships with 1 file
  • metadata.json
Commands it runs
New project
npm create mastra@latest
Existing project
npx mastra init --components agents,tools,workflows --llm openai
mastra dev              # Dev server + Studio at localhost:4111
mastra build            # Bundle to .mastra/output/
mastra build --studio   # Include Studio UI in build
mastra start            # Serve production build
mastra lint             # Validate project structure
mastra migrate          # Run DB migrations
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About this skill
What does the mastra skill do?

Use this skill when working with Mastra - the TypeScript AI framework for building agents, workflows, tools, and AI-powered applications. Triggers on creating agents, defining workflows, configuring memory, RAG pipelines, MCP client/server setup, voice integration, evals/scorers, deployment, and Mastra CLI commands. Also triggers on "mastra dev", "mastra build", "mastra init", Mastra Studio, or any Mastra package imports.

How do I install it?

Run `npx skills add majiayu000/claude-skill-registry --skill mastra --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

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