# Workflows overview

Workflows let you define complex sequences of tasks using clear, structured steps rather than relying on the reasoning of a single agent. They give you full control over how tasks are broken down, how data moves between them, and what gets executed when. Workflows run using the built-in execution engine by default, or can be deployed to [workflow runners](https://mastra.ai/docs/deployment/workflow-runners) like Inngest for managed infrastructure.

![Workflows overview](/assets/images/workflows-overview-4509c840549a01ff7386daa5101bda26.jpg)

## When to use workflows

Use workflows for tasks that are clearly defined upfront and involve multiple steps with a specific execution order. They give you fine-grained control over how data flows and transforms between steps, and which primitives are called at each stage.

> **Tip:** Watch an introduction to workflows, and how they compare to agents on [YouTube (7 minutes)](https://youtu.be/0jg2g3sNvgw).

## Core principles

Mastra workflows operate using these principles:

- Defining **steps** with `createStep`, specifying input/output schemas and business logic.
- Composing **steps** with `createWorkflow` to define the execution flow.
- Running **workflows** to execute the entire sequence, with built-in support for suspension, resumption, and streaming results.

## Creating a workflow step

Steps are the building blocks of workflows. Create a step using `createStep()` with `inputSchema` and `outputSchema` to define the data it accepts and returns.

The `execute` function defines what the step does. Use it to call functions in your codebase, external APIs, agents, or tools.

```typescript
import { createStep } from '@mastra/core/workflows'

const step1 = createStep({
  id: 'step-1',
  inputSchema: z.object({
    message: z.string(),
  }),
  outputSchema: z.object({
    formatted: z.string(),
  }),
  execute: async ({ inputData }) => {
    const { message } = inputData

    return {
      formatted: message.toUpperCase(),
    }
  },
})
```

> **Info:** Visit [`Step`](https://mastra.ai/reference/workflows/step) for a full list of configuration options.

### Using agents and tools

Workflow steps can also call registered agents or import and execute tools directly, visit the [Using Tools](https://mastra.ai/docs/agents/using-tools) page for more information.

## Creating a workflow

Create a workflow using `createWorkflow()` with `inputSchema` and `outputSchema` to define the data it accepts and returns. Add steps using `.then()` and complete the workflow with `.commit()`.

```typescript
import { createWorkflow, createStep } from "@mastra/core/workflows";
import { z } from "zod";

const step1 = createStep({...});

export const testWorkflow = createWorkflow({
  id: "test-workflow",
  inputSchema: z.object({
    message: z.string()
  }),
  outputSchema: z.object({
    output: z.string()
  })
})
  .then(step1)
  .commit();
```

> **Info:** Visit [Workflow Class](https://mastra.ai/reference/workflows/workflow) for a full list of configuration options.

### Understanding control flow

Workflows can be composed using a number of different methods. The method you choose determines how each step's schema should be structured. Visit the [Control Flow](https://mastra.ai/docs/workflows/control-flow) page for more information.

## Studio

Open [Studio](https://mastra.ai/docs/studio/overview) and select a workflow from the **Workflows** tab.

- **Graph view**: The center panel visualizes the workflow's steps and execution flow.
- **Input form**: The right sidebar generates a form from the workflow's `inputSchema`. Fill it in and start the run.
- **Live status**: During execution, the graph updates each step's status in real time. The sidebar shows the workflow's input, output, state, and logs.
- [**Time travel**](https://mastra.ai/docs/workflows/time-travel): After a run completes, replay individual steps to inspect or retry them.

## Workflow state

Workflow state lets you share values across steps without passing them through every step's inputSchema and outputSchema. Use state for tracking progress, accumulating results, or sharing configuration across the entire workflow.

```typescript
const step1 = createStep({
  id: 'step-1',
  inputSchema: z.object({ message: z.string() }),
  outputSchema: z.object({ formatted: z.string() }),
  stateSchema: z.object({ counter: z.number() }),
  execute: async ({ inputData, state, setState }) => {
    // Read from state
    console.log(state.counter)

    // Update state for subsequent steps
    setState({ ...state, counter: state.counter + 1 })

    return { formatted: inputData.message.toUpperCase() }
  },
})
```

> **Info:** Visit [Workflow State](https://mastra.ai/docs/workflows/workflow-state) for complete documentation on state schemas, initial state, persistence across suspend/resume, and nested workflows.

## Workflows as steps

Use a workflow as a step to reuse its logic within a larger composition. Input and output follow the same schema rules described in [Core principles](https://mastra.ai/docs/workflows/control-flow).

```typescript
const step1 = createStep({...});
const step2 = createStep({...});

const childWorkflow = createWorkflow({
  id: "child-workflow",
  inputSchema: z.object({
    message: z.string()
  }),
  outputSchema: z.object({
    emphasized: z.string()
  })
})
  .then(step1)
  .then(step2)
  .commit();

export const testWorkflow = createWorkflow({
  id: "test-workflow",
  inputSchema: z.object({
    message: z.string()
  }),
  outputSchema: z.object({
    emphasized: z.string()
  })
})
  .then(childWorkflow)
  .commit();
```

### Cloning a workflow

Clone a workflow using `cloneWorkflow()` when you want to reuse its logic but track it separately under a new ID. Each clone runs independently and shows up as a distinct workflow in logs and observability tools.

```typescript
import { cloneWorkflow } from "@mastra/core/workflows";

const step1 = createStep({...});

const parentWorkflow = createWorkflow({...})
const clonedWorkflow = cloneWorkflow(parentWorkflow, { id: "cloned-workflow" });

export const testWorkflow = createWorkflow({...})
  .then(step1)
  .then(clonedWorkflow)
  .commit();
```

## Registering a workflow

Register your workflow in the Mastra instance to make it available throughout your application. Once registered, it can be called from agents or tools and has access to shared resources such as logging and observability features:

```typescript
import { Mastra } from '@mastra/core/mastra'
import { testWorkflow } from './workflows/test-workflow'

export const mastra = new Mastra({
  workflows: { testWorkflow },
})
```

## Referencing a workflow

You can run workflows from agents, tools, the Mastra Client, or the command line. Get a reference by calling `.getWorkflow()` on your `mastra` or `mastraClient` instance, depending on your setup:

```typescript
const testWorkflow = mastra.getWorkflow('testWorkflow')
```

> **Info:** `mastra.getWorkflow()` is preferred over a direct import for two reasons:
>
> 1. It provides access to the Mastra instance configuration (logger, telemetry, storage, registered agents, and vector stores)
> 2. It provides full TypeScript type inference for workflow input and output schemas
>
> **Note:** Use `getWorkflow()` with the workflow's **registration key** (the key used when adding it to Mastra). While `getWorkflowById()` is available for retrieving workflows by their `id` property, it doesn't provide the same level of type inference.

## Running workflows

Workflows can be run in two modes: start waits for all steps to complete before returning, and stream emits events during execution. Choose the approach that fits your use case: start when you only need the final result, and stream when you want to monitor progress or trigger actions as steps complete.

**.start()**:

Create a workflow run instance using `createRun()`, then call `.start()` with `inputData` matching the workflow's `inputSchema`. The workflow executes all steps and returns the final result.

```typescript
const run = await testWorkflow.createRun()

const result = await run.start({
  inputData: {
    message: 'Hello world',
  },
})

if (result.status === 'success') {
  console.log(result.result)
}
```

**.stream()**:

Create a workflow run instance using `.createRun()`, then call `.stream()` with `inputData` matching the workflow's `inputSchema`. Iterate over `fullStream` to track progress, then await `result` to get the final workflow result.

```typescript
const run = await testWorkflow.createRun()

const stream = run.stream({
  inputData: {
    message: 'Hello world',
  },
})

for await (const chunk of stream.fullStream) {
  console.log(chunk)
}

// Get the final result (same type as run.start())
const result = await stream.result

if (result.status === 'success') {
  console.log(result.result)
}
```

### Workflow result type

Both `run.start()` and `stream.result` return a discriminated union based on the `status` property, which can be `success`, `failed`, `suspended`, `tripwire`, or `paused`. You can always safely access `result.status`, `result.input`, `result.steps`, and optionally `result.state` regardless of the status.

Additionally, depending on the status, different properties are available:

| Status      | Unique properties             | Description                                              |
| ----------- | ----------------------------- | -------------------------------------------------------- |
| `success`   | `result`                      | The workflow's output data                               |
| `failed`    | `error`                       | The error that caused the failure                        |
| `tripwire`  | `tripwire`                    | Contains `reason`, `retry?`, `metadata?`, `processorId?` |
| `suspended` | `suspendPayload`, `suspended` | Suspension data and array of suspended step paths        |
| `paused`    | _(none)_                      | Only common properties available                         |

To access status-specific properties, check the `status` first:

```typescript
const result = await run.start({ inputData: { message: 'Hello world' } })

if (result.status === 'success') {
  console.log(result.result) // Only available when status is "success"
} else if (result.status === 'failed') {
  console.log(result.error.message)
} else if (result.status === 'suspended') {
  console.log(result.suspendPayload)
}
```

### Workflow output

Here's an example of a successful workflow result, showing the `input`, `steps`, and `result` properties:

```json
{
  "status": "success",
  "steps": {
    "step-1": {
      "status": "success",
      "payload": {
        "message": "Hello world"
      },
      "output": {
        "formatted": "HELLO WORLD"
      }
    },
    "step-2": {
      "status": "success",
      "payload": {
        "formatted": "HELLO WORLD"
      },
      "output": {
        "emphasized": "HELLO WORLD!!!"
      }
    }
  },
  "input": {
    "message": "Hello world"
  },
  "result": {
    "emphasized": "HELLO WORLD!!!"
  }
}
```

## Restarting active workflow runs

When a workflow run loses connection to the server, it can be restarted from the last active step. This is useful for long-running workflows that might still be running when the server loses connection. Restarting a workflow run will resume execution from the last active step, and the workflow will continue from there.

### Restarting all active workflow runs of a workflow with `restartAllActiveWorkflowRuns()`

Use `restartAllActiveWorkflowRuns()` to restart all active workflow runs of a workflow. This helps restart all active workflow runs of a workflow, without having to manually loop through each run and restart.

```typescript
workflow.restartAllActiveWorkflowRuns()
```

### Restarting an active workflow run with `restart()`

Use `restart()` to restart an active workflow run from the last active step. This will resume execution from the last active step, and the workflow will continue from there.

```typescript
const run = await workflow.createRun()

const result = await run.start({ inputData: { value: 'initial data' } })

const restartedResult = await run.restart()
```

### Identifying active workflow runs

When a workflow run is active, it will have a `status` of `running` or `waiting`. You can check the workflow's `status` to confirm it's active, and use `active` to identify the active workflow run.

```typescript
const activeRuns = await workflow.listActiveWorkflowRuns()
if (activeRuns.runs.length > 0) {
  console.log(activeRuns.runs)
}
```

> **Note:** When running the local mastra server, all active workflow runs will be restarted automatically when the server starts.

## Using `RequestContext`

Use [RequestContext](https://mastra.ai/docs/server/request-context) to access request-specific values. This lets you conditionally adjust behavior based on the context of the request.

```typescript
export type UserTier = {
  'user-tier': 'enterprise' | 'pro'
}

const step1 = createStep({
  execute: async ({ requestContext }) => {
    const userTier = requestContext.get('user-tier') as UserTier['user-tier']

    const maxResults = userTier === 'enterprise' ? 1000 : 50

    return { maxResults }
  },
})
```

> **Info:** Visit [Request Context](https://mastra.ai/docs/server/request-context) for more information.

> **Tip:** For type-safe request context schema validation, see [Schema Validation](https://mastra.ai/docs/server/request-context).

## Related

For a closer look at workflows, see our [Workflow Guide](https://mastra.ai/guides/guide/ai-recruiter), which walks through the core concepts with a practical example.

- [Workflow State](https://mastra.ai/docs/workflows/workflow-state)
- [Control Flow](https://mastra.ai/docs/workflows/control-flow)
- [Suspend & Resume](https://mastra.ai/docs/workflows/suspend-and-resume)
- [Error Handling](https://mastra.ai/docs/workflows/error-handling)