Mastra

An agent is like a smart virtual employee you can give instructions to. Tell it what tools it can use — search the web, look up a customer record, send an email — and it figures out the steps on its own. You can even create a team of agents: one that researches, one that writes, and a supervisor that coordinates them. The agents keep working until the job is done.

When your AI needs to follow a strict process — first collect information, then validate it, then send it for approval, then execute — workflows let you define that process as a visual flow chart. Each step is guaranteed to run in the right order, and if human approval is needed, the workflow pauses, waits as long as necessary, and picks up exactly where it left off.

Tools are the actions your AI can take — looking up weather data, querying a database, calling an API, or running a calculation. You define what each tool does and what inputs it needs, and the AI decides when to use which tool. You can even have one AI agent call another agent as a tool, or kick off an entire workflow as a single tool call.

Instead of writing different code for every AI provider, you just change a single model name — like switching from 'openai/gpt-5.1' to 'anthropic/claude-opus-4'. Mastra automatically finds the right API key and connects. It's like a universal adapter: one plug, any AI model in the world.

MCP is the emerging universal standard for AI tools — think of it as USB-C for AI. Mastra can both plug into existing MCP tool servers (to use tools others have built) and publish your own AI agents and tools so other systems can use them. This means your AI can instantly connect to thousands of pre-built integrations.

Your AI remembers things — not just the current conversation, but your preferences, past interactions, and important facts. Working memory acts like a sticky note the AI keeps updated about you. Semantic recall lets it search past conversations by meaning, not just keywords. And observational memory automatically summarises long conversations so the AI stays sharp without running out of context space.

RAG lets your AI answer questions using your company's own documents — product manuals, knowledge bases, internal wikis. Mastra breaks documents into digestible pieces, converts them into searchable embeddings, stores them in a vector database, and retrieves the most relevant pieces when your AI needs to answer a question. The result is an AI that knows your business, not just generic internet knowledge.

How do you know if your AI is doing a good job? Mastra includes a built-in grading system. Every response can be automatically scored for quality, relevance, and safety. You can run these checks in real time on live conversations or batch-process historical data. It's like having a quality inspector watching every AI interaction and reporting back with scores and trends.

When your AI is running in production, you need to see what's happening under the hood — which model was called, how long it took, what tools were used, and whether anything went wrong. Mastra automatically records all of this and sends it to your monitoring platform of choice (Datadog, Sentry, etc.). It's like having a flight recorder for your AI: if something goes wrong, you can replay exactly what happened.

Studio is like a control room for your AI. Your developers open it in a browser and can chat with agents, step through workflows visually, test individual tools, view performance traces, and run quality checks — all without writing a single line of test code. Product managers can even use it to see how the AI behaves before it goes to customers.

For important decisions — approving a refund, sending a client email, or making a purchase — the AI pauses and asks a human to approve before continuing. The workflow remembers exactly where it stopped, even if the human takes hours or days to respond. This keeps humans in control of the high-stakes moments while the AI handles the routine work.

Whatever technology stack your product is built on — whether it's a Next.js website, an Express API, or a serverless function — Mastra fits right in. It works with all popular web frameworks and can be deployed anywhere: your own servers, AWS, Vercel, Cloudflare, or Mastra's own managed cloud service.