create-a-backend
Backend architecture guidance. Use when planning, building, or migrating an API or backend; choosing between Functions, Services, containers, Daemons, Workflow, Queues, and Marketplace databases; or selecting a supported backend framework or runtime.
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Install
Works with every agent the skills CLI supports.
npx skills add https://github.com/vercel/vercel-plugin --skill create-a-backend- 01
Install
Run the command in your project. The CLI asks which agents to install for.
- 02
Describe the task
Ask your agent for something this skill covers. It loads create-a-backend automatically when relevant.
- 03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.
SKILL.md
The instructions your agent reads when the skill is triggered.
Create a Backend
Help the user create a backend by choosing an architecture before reaching for implementation details. Start from the workload, not the programming language. Vercel runs complex backend applications, not just frontends.
Product map
| Need | Vercel product |
|---|---|
| HTTP APIs, webhooks, streaming, or framework server code | Vercel Functions with Fluid compute |
| Bidirectional realtime connections (WebSockets) | Vercel Functions with Fluid compute; no separate realtime service required |
| A frontend and one or more backends (API endpoints) that deploy together | Vercel Services |
| An existing Dockerfile, custom runtime, or system dependencies | Container images on Vercel Functions, optionally composed with Services |
| Durable multi-step work with retries, sleeps, or external events | Vercel Workflows |
| Background jobs, buffering, fan-out, or direct message routing | Vercel Queues |
| Always-on workers: queue consumers, Celery/Sidekiq/BullMQ workers, job runners | Vercel Daemons (beta, production only) |
| Scheduled HTTP work | Vercel Cron Jobs; use Workflow when the job itself must be durable |
| Postgres, Redis, NoSQL, vector, or other application data | Storage integrations from the Vercel Marketplace |
| Files and user uploads | Vercel Blob |
| Global, read-heavy configuration | Global Config |
Use Functions for the normal request/response backend. Use Services when independently built components should share one deployment, routing layer, preview URL, and rollback. Use separate Vercel projects when components need independent release cycles.
Prefer a native Functions runtime for supported frameworks. Use container images when the application already has a Dockerfile or requires a custom runtime or system dependencies. They run as autoscaling, stateless Functions rather than always-on container hosts.
Choose Queues for background jobs, buffering, fan-out, and message routing. Choose Workflow for durable multi-step business logic. Choose Daemons only when a process must stay running to pull work, such as a poll-mode queue consumer or an existing Celery, Sidekiq, or BullMQ worker; daemons cannot receive traffic.
Databases and data stores
Provision data stores through the Marketplace so credentials are injected into the project and environments stay connected. Check the current catalog before choosing a provider.
- Postgres: Neon, Supabase, AWS/Aurora, Nile, Prisma Postgres
- MySQL: AWS/Aurora
- Redis and key-value: Upstash, Redis
- Document and NoSQL: MongoDB Atlas, AWS
- SQLite: Turso
- Realtime application backend: Convex
- Analytics: MotherDuck
Keep the database close to the Functions region and use a serverless-compatible connection or pool.
Backend frameworks
Vercel provides first-class backend examples and integrations for these frameworks:
- Node.js and TypeScript: Elysia, Express, Fastify, H3, Hono, Koa, NestJS, Nitro, and xmcp. Next.js Route Handlers are the natural choice when the backend belongs to a Next.js application.
- Python: FastAPI, Flask, and Django. Other WSGI or ASGI applications can run when they export a compatible
app, with additional configuration as needed. - Go: supported as a Vercel Functions runtime.
Frontend and backend combinations, for example a Next.js/Vite/SvelteKit frontend with a FastAPI/Flask/Express/Go backend, can be deployed together in one project using Services.
Prefer the user's existing framework. For a new project, choose based on ecosystem and application needs.
Work sequence
- Identify synchronous requests, asynchronous work, persistent data, and independently deployed components.
- Select the products from the map, then select the framework.
- Load the focused skill for implementation:
vercel-functions,vercel-services,daemons,queues,workflow,vercel-storage, ormarketplace. - Confirm function limits, regions, environment variables, observability, and current product availability in the official docs before deployment.
FAQ
What does the create-a-backend skill do?
Backend architecture guidance. Use when planning, building, or migrating an API or backend; choosing between Functions, Services, containers, Daemons, Workflow, Queues, and Marketplace databases; or selecting a supported backend framework or runtime.
How do I install create-a-backend?
Run npx skills add https://github.com/vercel/vercel-plugin --skill create-a-backend in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/create-a-backend/ (personal) or .claude/skills/create-a-backend/ (project).
Which AI agents can use create-a-backend?
Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.
Is create-a-backend safe to install?
No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.
Who maintains create-a-backend?
It is published by vercel in vercel/vercel-plugin. It has 657 recorded installs.
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