Orchestrate AI agents, workflows, tools, memory, RAG, and MCP in TypeScript.
npx skills add https://github.com/Samuelca6399/AbsolutelySkilled --skill mastra-samuelca6399
Please help me install this Agent Skill. Skill: mastra Source: https://github.com/Samuelca6399/AbsolutelySkilled/tree/main/skills/mastra Command: npx skills add https://github.com/Samuelca6399/AbsolutelySkilled --skill mastra-samuelca6399
Mastra eliminates the complexity of wiring AI agents, tools, memory, RAG, and orchestration into a single working application, so you can ship reliable agent systems faster.
Use the Mastra skill to set up your project by running: npx mastra init --components agents,tools,workflows --llm openai
High-intent search queries and answers about installing and using this skill.
You can build AI agents with typed workflows in TypeScript by using the Mastra() constructor to orchestrate agents, createWorkflow() for multi-step pipelines, and createTool() for strongly-typed tool calls. It applies Zod schemas for input and output typing.
To add persistent memory and RAG to TypeScript AI agents, configure message history, working memory, and semantic recall within your agent setup. This framework supports vector-backed retrieval pipelines to enable RAG capabilities across threads and resources.
Yes, you can use MCP to connect external tools to your TypeScript AI workflows by configuring MCP client and server connections. This allows your AI agents to access and integrate external capabilities directly within the orchestration framework.
To set up a TypeScript project for AI agents, tools, and workflows, run the initialization command npx mastra init --components agents,tools,workflows --llm openai. This scaffolds the required project structure for deployment.
Yes, this framework supports Zod schemas for structuring multi-step AI pipelines. You use createStep() alongside createWorkflow() to define strongly-typed input and output schemas for each step of your agentic pipelines.
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