# VercelDeployer
[EN] Source: https://mastra.ai/docs/deployment/cloud-providers/vercel-deployer

The `VercelDeployer` class handles deployment of standalone Mastra applications to Vercel. It manages configuration, deployment, and extends the base [Deployer](/reference/deployer/) class with Vercel specific functionality.

## Installation

```bash copy
npm install @mastra/deployer-vercel@latest
```

## Usage example

```typescript title="src/mastra/index.ts" showLineNumbers copy
import { Mastra } from "@mastra/core/mastra";
import { VercelDeployer } from "@mastra/deployer-vercel";

export const mastra = new Mastra({
  // ...
  deployer: new VercelDeployer(),
});
```

> See the [VercelDeployer](/reference/deployer/vercel) API reference for all available configuration options.

### Optional overrides

The Vercel deployer can write a few high‑value settings into the Vercel Output API function config (`.vc-config.json`):

- `maxDuration?: number` — Function execution timeout (seconds)
- `memory?: number` — Function memory allocation (MB)
- `regions?: string[]` — Regions (e.g. `['sfo1','iad1']`)

Example:

```ts title="src/mastra/index.ts" showLineNumbers copy
deployer: new VercelDeployer({
  maxDuration: 600,
  memory: 1536,
  regions: ["sfo1", "iad1"],
});
```

## Continuous integration

After connecting your Mastra project’s Git repository to Vercel, update the project settings. In the Vercel dashboard, go to **Settings** > **Build and Deployment**, and under **Framework settings**, set the following:

- **Build command**: `npm run build` (optional)

### Environment variables

Before your first deployment, make sure to add any environment variables used by your application. For example, if you're using OpenAI as the LLM, you'll need to set `OPENAI_API_KEY` in your Vercel project settings.

> See [Environment variables](https://vercel.com/docs/environment-variables) for more details.

Your project is now configured with automatic deployments which occur whenever you push to the configured branch of your GitHub repository.

## Manual deployment

Manual deployments are also possible using the [Vercel CLI](https://vercel.com/docs/cli). With the Vercel CLI installed run the following from your project root to deploy your application.

```bash copy
npm run build && vercel --prod --prebuilt --archive=tgz
```

> You can also run `vercel dev` from your project root to test your Mastra application locally.

## Build output

The build output for Mastra applications using the `VercelDeployer` includes all agents, tools, and workflows in your project, along with Mastra specific files required to run your application on Vercel.

```
.vercel/
├── output/
│   ├── functions/
│   │   └── index.func/
│   │       └── index.mjs
│   └── config.json
└── package.json
```

The `VercelDeployer` automatically generates a `config.json` configuration file in `.vercel/output` with the following settings:

```json
{
  "version": 3,
  "routes": [
    {
      "src": "/(.*)",
      "dest": "/"
    }
  ]
}
```

## Next steps

- [Mastra Client SDK](/reference/client-js/mastra-client)


---
title: "Navigating the Dashboard | Mastra Cloud"
description: Details of each feature available in Mastra Cloud
---

import { MastraCloudCallout } from "@site/src/components/MastraCloudCallout";