VercelDeployer

The VercelDeployer class handles deployment of standalone Mastra applications to Vercel. It manages configuration, deployment, and extends the base Deployer class with Vercel specific functionality.

warning

Vercel Functions use an ephemeral filesystem. Remove any usage of LibSQLStore with file URLs from your Mastra configuration. Use in-memory storage (:memory:) or external storage providers like Turso, PostgreSQL, or Upstash.

Installation

npm

npm install @mastra/deployer-vercel@latest

pnpm

pnpm add @mastra/deployer-vercel@latest

Yarn

yarn add @mastra/deployer-vercel@latest

Bun

bun add @mastra/deployer-vercel@latest

Usage example

src/mastra/index.ts

import { Mastra } from "@mastra/core";
import { VercelDeployer } from "@mastra/deployer-vercel";

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

See the VercelDeployer 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:

src/mastra/index.ts

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 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. With the Vercel CLI installed run the following from your project root to deploy your application.

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:

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

Observability

To enable observability on Vercel, configure external storage (since Vercel's ephemeral filesystem doesn't support local file storage) and set up your preferred exporter(s).

Storage configuration

Use a PostgreSQL provider like Neon or Supabase for persistent storage:

src/mastra/index.ts

import { Mastra } from "@mastra/core";
import { PinoLogger } from "@mastra/loggers";
import { PostgresStore } from "@mastra/pg";
import { Observability, DefaultExporter, CloudExporter } from "@mastra/observability";

export const mastra = new Mastra({
  logger: new PinoLogger(),
  storage: new PostgresStore({
    connectionString: process.env.DATABASE_URL!,
  }),
  observability: new Observability({
    configs: {
      default: {
        serviceName: "my-mastra-app",
        exporters: [
          // Choose based on your observability platform:
          new DefaultExporter(), // Your storage → Mastra Studio
          new CloudExporter(),   // Mastra Cloud
          // new ArizeExporter(),   // Arize
          // new LaminarExporter(), // Laminar
          // etc.
        ],
      },
    },
  }),
  // ... agents, tools, workflows
});

See the Tracing documentation for all available exporters.

Environment variables

Add these to your Vercel project settings based on your configuration:

Variable	Description
DATABASE_URL	PostgreSQL connection string (required for storage)
MASTRA_CLOUD_ACCESS_TOKEN	Required if using CloudExporter
OPENAI_API_KEY	Your LLM provider API key

Flushing traces

In serverless environments, call flush() to ensure traces are exported before the function completes:

app/api/chat/route.ts

import { mastra } from "@/mastra";

export async function POST(req: Request) {
  const { message } = await req.json();
  const agent = mastra.getAgent("myAgent");

  const result = await agent.generate([{ role: "user", content: message }]);

  // Flush traces before the serverless function completes
  const observability = mastra.getObservability();
  await observability.flush();

  return Response.json(result);
}

For more details on tracing configuration, see the Tracing documentation.

Next steps

• Mastra Client SDK