A TypeScript framework + cloud for building, observing, and orchestrating AI agents & workflows with unified APIs and dev-friendly tools.
A TypeScript framework + cloud for building, observing, and orchestrating AI agents & workflows with unified APIs and dev-friendly tools.
You can use Mastra when you want to build AI agents in a modern JavaScript/TypeScript stack—whether for prototyping or production. It offers agents that maintain memory, workflows (durable graph-based state machines), observability for agent behaviour, vector/RAG tools, and unified provider APIs that let you switch LLMs easily. Great for dev teams building multi-agent apps, copilots, RAG pipelines, or any system needing orchestration, tracing, and modular agents.
Is this a good fit for my stack? Use Cases Building an AI copilot that accesses your company’s data and tools via agent workflows
Constructing conversational agents with memory that can recall past interactions
Automating business processes with multiple steps, retries, conditional logic (e.g. email + API calls + decision branching)
Implementing RAG search assistants over your documents or knowledge base
Monitoring and debugging AI agents and workflows via observability and tracing
Rapid prototyping and productionizing of agentic systems with JS/TS teams
Standout Features TypeScript-first agent & workflow framework with unified APIs
Durable workflows: graph-based state machines with pauses, retries, human-in-the-loop support
Built-in observability: tracing, evaluation, performance / cost metrics step-by-step
Seamless RAG support: vector store + embeddings + metadata filtering + reranking
Unified provider abstraction (swap LLMs easily)
Developer-friendly UX: CLI, templates, structured outputs, observability dashboards
Tasks it helps with Create agents in TypeScript/Node with memory and tool-calling
Define and run workflows that chain LLM/tool/agent steps with branching/retries
Embed RAG capabilities (vector store, embeddings, query, rerank) in agents
Switch LLM providers via a unified API/interface
Observe/tracing agent executions (tool calls, memory usage, performance, errors)
Evaluate agent output (using cloneable scorers, structured output APIs, etc.)
Who is it for? Software Engineer, AI Engineer, Full-Stack Developer, Product Engineer, CTO, DevOps Engineer
Overall Web Sentiment People love it
Time to value Quick Setup (< 1 hour to try simple agents; more time to configure production workflows and observability) Mastra, TypeScript agent framework, workflows, RAG, AI agents, unified provider API, observability, memory, vector store
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