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Cloud & infrastructure

Vercel CLI for coding agents

Deployments, env vars, project linking, logs, aliases, and preview deployments.

Open the official project ↗

This article follows the official documentation. We haven’t tested this tool for a hands-on review.

A coding agent with shell access in a Vercel project can use Vercel CLI to inspect deployments. The agent can also read logs, manage environment variables, and deploy code. The CLI is Vercel’s command-line tool: it runs on your machine, authenticates to your Vercel account, and sends requests to Vercel when a command needs project or deployment data.

For a safe first task, ask the agent to list the project’s deployments and inspect one deployment URL. These commands only read data. When the agent deploys or changes project settings, Vercel CLI sends write requests to Vercel, so keep those actions separate and approve them explicitly.

Install and authenticate

Install the CLI with npm, which downloads it to your machine:

npm install --global vercel

Then sign in:

vercel login

Vercel’s installation and login documentation explains these steps. Sign-in connects the CLI to your Vercel account. The account must have access to the project the agent will inspect. Complete authentication yourself; do not paste a login token or other secret into the agent’s prompt. For automated environments, provide credentials through the environment’s secret-management mechanism.

From the repository directory, link the local folder to its Vercel project if it is not already linked:

vercel link

The CLI asks you to choose or identify a project and saves the project link on your machine. When you link a project, the CLI contacts Vercel and creates local configuration without deploying code. See the vercel link command for its options.

Inspect a deployment

After linking the project, vercel ls lists its deployments. Use a deployment URL from that list with vercel inspect to retrieve details about that deployment. Both commands contact Vercel without deploying code or changing project settings.

cd /path/to/repository
vercel ls

Then set DEPLOYMENT_URL to a real URL from the listing. The value below is a placeholder, not a usable URL:

export DEPLOYMENT_URL='REPLACE_WITH_DEPLOYMENT_URL'
vercel inspect "$DEPLOYMENT_URL"

The CLI prints deployment information, including its status. The exact output depends on the deployment and CLI version; these examples do not assume particular output fields or results. Vercel documents the vercel ls and vercel inspect commands separately.

A focused agent prompt could be:

Use Vercel CLI in this linked repository to list deployments and inspect the deployment URL I provide. Report the deployment status and relevant details. Do not deploy code or change environment variables.

The commands in this example are documentation-based and have not been run for this article.

Keep inspection separate from deployment

Vercel CLI can also change your project. Vercel CLI deploys the project as a preview when you run vercel; with --prod, it deploys the project to production. A preview deployment is a hosted deployment for review before production. The deployment command documentation covers these options.

After inspection, review the proposed code and decide whether to create a preview. Ask the agent to run the deployment command only after you approve that step. Require separate, explicit approval before deploying to production.

Vercel also offers an optional plugin for AI coding agents, which adds Vercel-specific guidance and commands to supported tools. The plugin complements the CLI; it does not replace project authentication or the effects of CLI commands. For Marketplace integrations, Vercel documents agent-oriented discover and guide commands. The discover command can return JSON output through --format=json. Integration setup can involve service changes or human decisions such as accepting terms, so an agent should ask before proceeding.

Tool details come from awesome-ai-cli.