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.
Installation
npm install @mastra/deployer-vercel@latest
Usage example
import { Mastra } from "@mastra/core/mastra";
import { VercelDeployer } from "@mastra/deployer-vercel";
export const mastra = new Mastra({
// ...
deployer: new VercelDeployer()
});
See the VercelDeployer API reference for all available configuration options.
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.
- 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": "/"
}
]
}