Vercel Cli logo

Vercel Cli

Organization
vercel
vercel-cli

Deploy, manage, inspect, and troubleshoot Vercel projects from the command line. Use for Vercel deployments, Vercel Toolbar comments, build failures, projects and teams, environment variables, domains and DNS, logs, metrics, Speed Insights, Core Web Vitals, request traces, usage, activity, alerts, firewall rules, cache, cron jobs, deploy hooks, Edge Config, feature flags (`vercel flags`), integrations, connectors, Blob storage, Container Registry (VCR), microfrontends, rolling releases, custom environments, Sandbox, agent/MCP setup, preview access, local development, or `vercel api` fallback.

Overview

Publishervercel
Repositoryvercel-plugin
Skill namevercel-cli
Stars
286
Forks
56
Bundled files
27
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 27 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by vercel on GitHub. Read the source before you install it.

Installation

Install the Vercel Cli AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/vercel/vercel-plugin.git /tmp/vercel-plugin
mkdir -p .claude/skills
cp -r /tmp/vercel-plugin/skills/vercel-cli/upstream .claude/skills/vercel-cli
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Vercel Cli in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Vercel Cli on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Vercel Cli is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Vercel CLI Skill

The Vercel CLI (vercel or vc) deploys, manages, and develops projects on the Vercel platform from the command line. Use vercel <command> --help for full flag details on any command.

The installed CLI help is the source of truth for obscure or newly added flags. If a command example here is not enough, check vercel <command> --help before acting instead of guessing.

Parse only stdout for URLs and JSON. Warnings, progress, and --help print to stderr; merge streams only when searching help text. Some help commands exit 2 after printing usage, so treat printed usage as a successful help read.

In agent/non-interactive mode, many commands report errors and required confirmations as a single JSON object on stdout with status, reason, hint, and next (runnable follow-up commands). Prefer a suggested next command over composing a retry only after confirming that it preserves the user's intended target and authorization; do not automatically run linking, authentication, or mutation follow-ups. Read commands such as list, logs, inspect, and api keep their normal output shape.

Critical: Project Linking

Project context depends on the command's working directory. Before a consequential read or mutation, run vercel project inspect --non-interactive from the intended directory and confirm the reported owner and project. This command resolves only existing context in non-interactive mode; stop on link_required or a target mismatch instead of linking automatically.

Many project-aware commands also accept --project <name-or-id> with --scope <team> for an explicit, one-command target. Confirm that target and scope preserve the user's intent before using them.

  • <cwd>/.vercel/project.json: Created by vercel link. This exact working-directory link wins over a repository link. The CLI does not generally inherit a root project.json when run from an arbitrary subdirectory.
  • <repo-root>/.vercel/repo.json: Created by vercel link --repo. The CLI selects the deepest project directory that contains the working directory.
  • Unmatched repository path: If no repo mapping contains the working directory, interactive repo resolution prompts among the configured projects. Non-interactive repo resolution currently selects the only configured project or remains unresolved when multiple choices exist. Commands that set up projects may then enter a linking flow, so non-interactive mode is not generally fail-closed.

Being inside an app directory is not proof that the intended project was selected. Check the resolved project explicitly, especially when a repo mapping does not cover that directory.

vercel whoami --format json identifies the authenticated user and effective team; plain non-TTY vercel whoami prints only the username. Neither verifies the linked project. Read-only project commands can still require login or team SAML re-authentication and open a browser/device flow. Ask the user to complete that flow deliberately before continuing.

Quick Start

bash
npm i -g vercel
vercel login
vercel link              # single project
# OR
vercel link --repo       # monorepo
vercel pull
vercel dev        # local development
vercel deploy     # preview deployment
vercel --prod     # production deployment

Decision Tree

Use this to route to the correct reference file:

  • Deploy, redeploy, forced builds, no-cache builds, or deployment source/provenancereferences/deployment.md
  • Rolling releases, deploy hooks, cron jobs, cache, git connection, Edge Config, redirects, custom environmentsreferences/project-infra.md
  • Local developmentreferences/local-development.md
  • Environment variablesreferences/environment-variables.md
  • CI/CD automationreferences/ci-automation.md
  • Domains or DNSreferences/domains-and-dns.md
  • Projects or teamsreferences/projects-and-teams.md
  • Vercel Toolbar comments (vercel comments)references/comments.md
  • Build failures, deployment errors, logs, metrics, Speed Insights, Core Web Vitals, activity, performance, preview access, or production debuggingreferences/monitoring-and-debugging.md
  • Alerts, usage, contracts, billing purchases, tokens, telemetry, or CLI upgradesreferences/platform-ops.md
  • Blob storagereferences/storage.md
  • Container Registry (vercel vcr: repositories, images, tags, docker/podman/buildah login, push/pull)references/container-registry.md
  • Integrations (databases, storage, etc.)references/integrations.md
  • Connectors (vercel connect)references/connectors.md
  • Routing rulesreferences/routing.md
  • Firewall (WAF rules, IP blocks, rate limiting)references/firewall.md
  • Access a preview deployment → use vercel curl (see references/monitoring-and-debugging.md)
  • CLI command is unavailable or output is missing required fields → use vercel api after first-class CLI paths are unavailable or insufficient (see references/advanced.md)
  • Node.js backends (Express, Hono, etc.)references/node-backends.md
  • Monorepos (Turborepo, Nx, workspaces)references/monorepos.md
  • Bun runtimereferences/bun.md
  • Feature flags (vercel flags: create, inspect, set, split, rollout, rules, segments, sdk-keys)references/flags.md
  • Microfrontendsreferences/microfrontends.md
  • Sandboxreferences/sandbox.md
  • Agent, MCP, skills discovery, or AI Gatewayreferences/agent-and-ai.md
  • Captured request traces (vercel traces, including --open / --view)references/advanced.md
  • Advanced (vercel api fallback, webhooks)references/advanced.md
  • Global flagsreferences/global-options.md
  • First-time setupreferences/getting-started.md

Anti-Patterns

  • Wrong link type in monorepos with multiple projects: vercel link creates project.json, which only tracks one project. Use vercel link --repo instead. When things break, check .vercel/ first.
  • Letting commands auto-link in monorepos: Many commands implicitly run vercel link if .vercel/ doesn't exist. This creates project.json, which may be wrong. Run vercel link (or --repo) explicitly first.
  • Assuming an app subdirectory determines the project: Verify with vercel project inspect --non-interactive; an unmatched repo path can currently fall back to the sole configured project in non-interactive mode.
  • Using vercel whoami as linked-project verification: vercel whoami --format json reports authentication and team context, not the selected project.
  • Forgetting non-interactive flags in plain CI runs: detected agents get --non-interactive by default, but plain CI does not — pass it explicitly there, and add --yes only for commands that require confirmation.
  • Using vercel deploy after vercel build without --prebuilt: The build output is ignored.
  • Using vercel redeploy for no-cache rebuilds: vercel redeploy does not expose a no-cache flag; use vercel deploy --force without --with-cache when you need a fresh deployment that does not retain build cache.
  • Hardcoding tokens in flags: Use VERCEL_TOKEN env var instead of --token.
  • Disabling deployment protection: Use vercel curl instead to access preview deploys.
  • Using vercel api too early: Prefer first-class CLI commands when they expose the needed data or mutation.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Vercel Cli AI skill do?

Deploy, manage, inspect, and troubleshoot Vercel projects from the command line. Use for Vercel deployments, Vercel Toolbar comments, build failures, projects and teams, environment variables, domains and DNS, logs, metrics, Speed Insights, Core Web Vitals, request traces, usage, activity, alerts, firewall rules, cache, cron jobs, deploy hooks, Edge Config, feature flags (`vercel flags`), integrations, connectors, Blob storage, Container Registry (VCR), microfrontends, rolling releases, custom environments, Sandbox, agent/MCP setup, preview access, local development, or `vercel api` fallback.

Why use Vercel Cli on TypingMind?

Because you install it once and use it with any model. Vercel Cli is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Vercel Cli in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/vercel/vercel-plugin/tree/main/skills/vercel-cli/upstream. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Vercel Cli?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Vercel Cli?

As many as you like. As long as a model supports skills, you can use Vercel Cli with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Vercel Cli AI skill free?

It is published on GitHub by vercel. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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