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Vercel Services

Organization
vercel
vercel-services

Configure and troubleshoot Vercel Services for multiple frontends and backends in one project. Use when composing a polyglot or multi-service application on one Vercel deployment; defining the `services` key, service-targeted rewrites, or service bindings in `vercel.json`; or running all services with `vercel dev`.

Overview

Publishervercel
Repositoryvercel-plugin
Skill namevercel-services
Stars
286
Forks
56
Bundled files
Instructions only
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 on GitHub. Read the source before you install it.

Installation

Install the Vercel Services 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-services .claude/skills/vercel-services
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Vercel Services 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 Services 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 Services 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 Services

Use the services model whenever one application is made of multiple tightly coupled components, such as a frontend plus a backend, that should deploy to one Vercel project.

Services build independently but ship together as one deployment. That buys skew protection between frontend and backend, preview environments where every service is in sync, atomic deployments and rollbacks of the whole app, and private service-to-service communication through bindings. Public traffic enters through one ordered route table.

Choose the right structure

NeedUse
Multiple tightly coupled components, such as a frontend and a backend, that should ship as one appVercel Services
One framework can own the whole app, such as Next.js with Route HandlersOne normal Vercel project without Services
Teams own their services and deploy and roll back on their own cadenceSeparate Vercel projects in a monorepo
Independently deployed frontends must render as one siteVercel Microfrontends

The benefits and the drawback are the same fact: every deployment ships all services together. Reach for separate projects only when you specifically need to deploy or roll back one service independently of the others.

Do not introduce Services just to split one framework into arbitrary processes. Use it when an independently built component has a real runtime, framework, dependency, or ownership reason to exist.

Define services and public ingress

Each service requires a root relative to vercel.json. Let Vercel detect the framework unless pinning it is necessary. Set entrypoint relative to the service root when the runtime needs one.

json
{
  "services": {
    "frontend": {
      "root": "apps/web",
      "bindings": [
        {
          "type": "service",
          "service": "backend",
          "format": "url",
          "env": "BACKEND_INTERNAL_URL"
        }
      ]
    },
    "backend": {
      "root": "apps/backend",
      "entrypoint": "main:app"
    }
  },
  "rewrites": [
    { "source": "/api/(.*)", "destination": { "service": "backend" } },
    { "source": "/(.*)", "destination": { "service": "frontend" } }
  ]
}

The top-level rewrites expose the services. A service without a matching top-level rewrite is private: not reachable from the public internet, only through bindings.

Keep configuration ownership clear:

  • Keep public rewrites, redirects, headers, and other URL behavior at the top level.
  • Put functions, installCommand, buildCommand, devCommand, ignoreCommand, outputDirectory, and framework settings on the service that owns them.
  • Put service-local headers, redirects, rewrites, or routes inside a service only when they should run after public ingress selects that service.
  • Set runtime: "container" when a service must build from a Dockerfile or OCI image. Use entrypoint for a nonstandard Dockerfile and command to override the image command.

Route requests correctly

Top-level rewrites are evaluated in order. Put specific rules before the catch-all.

Routing into a service is final. If the selected service returns a 404 or 405, Vercel does not try the next top-level rewrite.

Split the URL namespace by what the frontend needs:

  • Frontends without their own server routes, such as Vite or Create React App builds, let the backend own all of /api.
  • Frameworks with their own API routes, such as Next.js, share the namespace: send only a sub-namespace such as /api/v1/(.*) or specific prefixes such as /api/users/(.*) to the backend, and let the framework keep the rest.

The service receives the original request path. With the example above, GET /api/users reaches backend as /api/users, not /users. Either make the backend handle the prefix, such as FastAPI root_path, or strip it with a service-scoped rewrite:

json
{
  "services": {
    "backend": {
      "root": "apps/backend",
      "entrypoint": "main:app",
      "rewrites": [
        { "source": "/api/:path(.*)?", "destination": "/:path" }
      ]
    }
  }
}

An SPA service that serves a static index.html, such as a Vite build, needs a service-scoped catch-all so deep links resolve:

json
{
  "services": {
    "frontend": {
      "root": "apps/web",
      "rewrites": [
        { "source": "/(.*)", "destination": "/index.html" }
      ]
    }
  }
}

Do not set path on a service destination. The field is accepted by the schema but has no effect at request time. Reshape paths with a service-scoped rewrite or a request.path transform in the service's own routes instead.

Serve a service on a subdomain

Host-matched top-level rewrites can put a service on its own subdomain, such as api.example.com, while the catch-all serves the frontend:

json
{
  "rewrites": [
    {
      "source": "/(.*)",
      "has": [{ "type": "host", "value": "api.example.com" }],
      "destination": { "service": "backend" }
    },
    { "source": "/api/(.*)", "destination": { "service": "backend" } },
    { "source": "/(.*)", "destination": { "service": "frontend" } }
  ]
}

Subdomains resolve only where that domain is attached: production, or a custom environment with a custom domain. Preview deployments get a single generated URL, so keep the subpath rewrite alongside the host rule and point the frontend at the relative path, for example NEXT_PUBLIC_API_URL=/api, so every preview calls its own deployment.

Call services privately with bindings

Declare a binding on the caller service, name the target service, and choose the environment variable that receives the generated URL. Do not hardcode deployment hostnames or manually set binding variables.

ts
const url = new URL('/api/users', process.env.BACKEND_INTERNAL_URL);
const response = await fetch(url);

Bindings are deployment-aware and do not create public routes. They are available to functions at runtime, not during builds or in Routing Middleware. Internal calls skip the public Firewall, Deployment Protection, top-level middleware, and CDN pipeline.

Public exposure is decided only by top-level rewrites. A service with no top-level rewrite is private: it is unreachable from the public internet and only accessible through its bindings. A service with both bindings and a top-level rewrite is also reachable publicly, so do not assume binding-only access implies the routes are protected.

A binding grants network reachability, not application authentication. Add service-level authorization when the target must verify the caller.

Native Go and Rust runtime services cannot currently consume bindings. Build those callers as container services when they need bindings. Node.js and Python services can use bindings directly.

Develop and deploy

Run every service and inject local binding variables:

bash
vercel dev

Use local-only mode when cloud authentication is unnecessary:

bash
vercel dev -L

Deploy the project normally with vercel or Git integration. All services participate in the same preview and production deployment.

Troubleshoot

  • No public traffic reaches a service: add a top-level rewrite targeting it.
  • The wrong service receives a request: reorder rewrites so the most specific rule comes first and the catch-all is last.
  • A backend returns 404: confirm its routes include the public prefix because Vercel preserves the original request path, or strip the prefix with a service-scoped rewrite.
  • An SPA returns 404 on deep links: add a service-scoped catch-all rewrite to /index.html.
  • A subdomain works in production but not in previews: preview URLs have a single host, so host rules never match there. Keep a subpath rewrite to the same service and use the relative URL in the frontend.
  • A binding variable is missing: declare the binding on the caller and access it from runtime function code, not build code or middleware.
  • Build settings are ignored or rejected: move top-level build and runtime fields into the owning service.
  • Framework detection is wrong: set that service's framework or entrypoint explicitly instead of changing the whole project.

Related skills

  • Deployment commands and CI: ⤳ skill: deployments-cicd
  • Function runtime behavior and limits: ⤳ skill: vercel-functions
  • Independent frontend deployments: ⤳ skill: microfrontends

Frequently asked questions

What does the Vercel Services AI skill do?

Configure and troubleshoot Vercel Services for multiple frontends and backends in one project. Use when composing a polyglot or multi-service application on one Vercel deployment; defining the `services` key, service-targeted rewrites, or service bindings in `vercel.json`; or running all services with `vercel dev`.

Why use Vercel Services on TypingMind?

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

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

Which AI models can use Vercel Services?

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 Services?

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

Is the Vercel Services 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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