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Protected Vercel Deployments

OrganizationPopular
vercel-labs
protected-vercel-deployments

Access and test Vercel deployments protected by Vercel Authentication, SSO, or Deployment Protection with agent-browser. Use when a preview or production URL redirects to a Vercel login page, returns a protection 401 or 403, or needs short-lived Trusted Sources OIDC authentication instead of a static bypass secret or public exception.

Overview

Publishervercel-labs
Repositoryagent-browser
Skill nameprotected-vercel-deployments
Stars
42.8K
Forks
2.9K
Bundled files
Instructions only
LicenseApache-2.0
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.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

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

Installation

Install the Protected Vercel Deployments 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-labs/agent-browser.git /tmp/agent-browser
mkdir -p .claude/skills
cp -r /tmp/agent-browser/skill-data/protected-vercel-deployments .claude/skills/protected-vercel-deployments
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Protected Vercel Deployments 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 Protected Vercel Deployments 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 Protected Vercel Deployments 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.

Protected Vercel deployments

Use the caller's existing Vercel identity and a short-lived OIDC token. Do not disable Deployment Protection, make the deployment public, or ask for a static bypass secret first.

Same-project preview

A local development token for the target project can access that project's protected Preview deployments through the default Trusted Sources self-access rule. No Trusted Sources configuration is normally required.

Confirm the local identity and Vercel CLI version:

bash
vc whoami
vc --version

Require Vercel CLI 53.3.0 or newer before running vc project token. Versions 50.25.0 through 53.2.x write the token to stderr, so command substitution captures nothing and the credential can appear in logs. If the installed version is older, stop and ask the user to upgrade it. Do not attempt to capture or recover the token from stderr.

Set the target project and scope explicitly. If they cannot be inferred safely, ask the user. In a directory whose existing .vercel/project.json link has been verified against the target, vc project token without a project name is also valid. Do not run vc link merely to get an OIDC token: current Vercel CLI versions also pull development variables into .env.local when linking.

Create a named browser session, mint a development OIDC token with the Vercel CLI, then inject it without printing or persisting it:

bash
export AGENT_BROWSER_SESSION="$(agent-browser session id --scope worktree --prefix vercel-preview)"
export VERCEL_PREVIEW_URL="https://my-app.vercel.app"
export VERCEL_PROJECT="my-app"
export VERCEL_SCOPE="my-team"

(
  TOKEN="$(vc project token "$VERCEL_PROJECT" --scope "$VERCEL_SCOPE")"
  test -n "$TOKEN"
  agent-browser open "$VERCEL_PREVIEW_URL" --headers \
    "{\"x-vercel-trusted-oidc-idp-token\":\"$TOKEN\"}"
)

agent-browser snapshot -i

Continue the normal workflow in that same session. The header is scoped to the target origin and applies to the document, scripts, styles, fonts, and in-page requests. If the browser session is closed or restarted, repeat the authenticated open command.

Never print the token, paste it into source, or save it in an environment file.

Other environments and callers

Trusted Sources configuration is needed when:

  • a local development token must reach a protected Production deployment;
  • the caller belongs to another Vercel project or team;
  • the target project's self-access rules were customized; or
  • Vercel returns TRUSTED_SOURCES_ENVIRONMENT_MISMATCH.

There is no supported Vercel CLI or public REST API for editing Trusted Sources rules. An authorized human must open the target project's Settings → Deployment Protection → Trusted Sources and add only the required caller and environment mapping. A local token has the development environment, so protected Production access requires development to production.

Stop and hand off the exact rule to the human. Do not use browser automation to change access control, and do not broaden unrelated environment mappings. Retry the authenticated open after the human confirms the rule is saved.

Human intervention boundaries

The same-project development to Preview path should run without human intervention when the Vercel CLI is already authenticated and the target project and scope are known. A human is needed only when:

  • the Vercel CLI has no authenticated identity and no existing VERCEL_TOKEN; interactive vc login requires the user;
  • the installed Vercel CLI is older than 53.3.0 and must be upgraded before token minting;
  • the correct target project or scope cannot be inferred safely for token minting;
  • a Trusted Sources rule must be added or changed; the dashboard is the only supported management surface, and this changes access control;
  • Secure Backend Access with OIDC Federation was disabled on the calling project and must be re-enabled in Settings → Security; or
  • the static-secret fallback must be enabled or rotated and the agent needs explicit authorization for that access-control change. After approval, the agent can use vc project protection instead of requiring dashboard interaction.

The agent can diagnose each case and state the exact action required, then continue after the user confirms completion.

Use the correct header

Send the Vercel-issued token as:

text
x-vercel-trusted-oidc-idp-token: <VERCEL_OIDC_TOKEN>

Do not substitute x-vercel-oidc-token. That header carries workload identity into a Vercel Function; it does not authenticate an inbound request through Deployment Protection.

Diagnose failures

  • Redirect to vercel.com/login: Deployment Protection did not accept the request.
  • TRUSTED_SOURCES_ENVIRONMENT_MISMATCH: the token is valid, but its caller environment cannot reach the target environment.
  • Application 401 or 403 after protection passes: debug the application's own authentication separately.
  • Application 404 on a deliberately missing route: the request passed Deployment Protection and reached the application.

Static-secret fallback

Use Protection Bypass for Automation only when OIDC is not viable or the tool cannot send the Trusted Sources header. Enabling or rotating it changes access control, so obtain explicit authorization first. Create a dedicated secret so it can be rotated independently, keep it in an environment variable, and pass it as a header:

bash
vc project protection enable <project> --protection-bypass \
  --protection-bypass-secret "$VERCEL_AUTOMATION_BYPASS_SECRET"

agent-browser open "$VERCEL_PREVIEW_URL" --headers \
  "{\"x-vercel-protection-bypass\":\"$VERCEL_AUTOMATION_BYPASS_SECRET\",\"x-vercel-set-bypass-cookie\":\"true\"}"

The cookie directive creates a reusable _vercel_jwt cookie. Treat saved browser state containing that cookie as a credential.

Avoid dead ends

  • There is no vercel share CLI command. Shareable Links are intended for people and are not the automation path.
  • vercel curl is useful for HTTP requests, but it cannot render and interact with a page.
  • Deployment Protection Exceptions make the domain public. Do not use them merely to unblock an agent.
  • Do not expose OIDC tokens, bypass secrets, authenticated URLs, or saved state in logs, screenshots, source files, or user-facing output.

Frequently asked questions

What does the Protected Vercel Deployments AI skill do?

Access and test Vercel deployments protected by Vercel Authentication, SSO, or Deployment Protection with agent-browser. Use when a preview or production URL redirects to a Vercel login page, returns a protection 401 or 403, or needs short-lived Trusted Sources OIDC authentication instead of a static bypass secret or public exception.

Why use Protected Vercel Deployments on TypingMind?

Because you install it once and use it with any model. Protected Vercel Deployments 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 Protected Vercel Deployments in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/vercel-labs/agent-browser/tree/main/skill-data/protected-vercel-deployments. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Protected Vercel Deployments?

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 Protected Vercel Deployments?

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

Is the Protected Vercel Deployments AI skill free?

Yes. It is published on GitHub by vercel-labs under the Apache-2.0 license. 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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