Hosting AI on Vercel - v0 by Vercel

Yes! Vercel provides excellent infrastructure for building and deploying AI agents. Here's how you can host AI agents on Vercel:

Building AI Agents with the AI SDK

Vercel's AI SDK provides a unified interface for building agentic systems with support for:

Sequential Processing - Steps executed in order
Parallel Processing - Independent tasks run simultaneously
Evaluation/Feedback Loops - Results checked and improved iteratively
Orchestration - Coordinating multiple components
Routing - Directing work based on context

import { generateText } from "ai"
import { openai } from "@ai-sdk/openai"

const { text } = await generateText({
  model: openai("gpt-4o"),
  prompt: "What is love?"
})

Deployment Options

1. Fluid Compute (Recommended)

Vercel's next-generation compute platform is ideal for AI agents because it:

Scales automatically while minimizing cold starts
Runs background tasks after responding to users (via after or waitUntil)
Handles concurrent workloads cost-effectively
Supports ephemeral processes without typical serverless timeouts 1

2. Single File Deployments

You can deploy single JavaScript or TypeScript files that run single or multi-step workflows, with integrations to databases and AI inference through the Vercel Marketplace 1

Model Context Protocol (MCP) Support

Building MCP Servers

Vercel offers templates for creating MCP servers:

Model Context Protocol with Vercel Functions
Model Context Protocol with Next.js

MCP servers on Vercel can:

List Vercel projects
Create deployments
Upload files for deployments
Manage domains and DNS 1

MCP Client Integration

You can connect to MCP servers using Vercel's AI SDK, allowing your AI applications to discover and call tools through a standardized interface 1

Creating Deployments from AI Agents

AI agents can programmatically create and manage Vercel deployments using:

Vercel SDK

import { Vercel } from "@vercel/sdk";

const vercel = new Vercel({ bearerToken: "<YOUR_BEARER_TOKEN>" });

// Upload files and create deployment
const deployment = await vercel.deployments.createDeployment({
  teamId,
  requestBody: {
    files: [{ file: ".vercel/source.tgz", sha: fileSha }],
    projectSettings: { framework: "nextjs" },
    name: `ai-generated-${Date.now().toString(36)}`,
  },
});

REST API

Direct API calls for uploading build artifacts and creating deployments 1

Vercel CLI

Command-line deployment within automated workflows 1

User Deployment Claims

A powerful feature allows AI agents to create deployments on your account, then let end users "claim" ownership through a simple URL flow:

Agent creates deployment
Generates claim URL
User visits URL and transfers ownership to their account 1

Real-World Examples

Several production AI applications are already running on Vercel's agent infrastructure:

v0.dev - Vercel's agent for building web apps
glif.app - Fun AI apps anyone can build
ohara.ai - Create apps & games with ownership stakes
a0.dev - Mobile apps in minutes
gumloop.com - AI automation framework 1

Integration Ecosystem

Vercel has first-class support for AI integrations including:

Storage: Vercel Blob, Supabase, Neon, Upstash
AI Providers: Fal, Grok, xAI, DeepInfra
Background Tasks: Inngest, Upstash Qstash 1

The combination of Fluid compute, the AI SDK, MCP support, and deployment automation makes Vercel an excellent platform for hosting sophisticated AI agents that can scale automatically and integrate with the broader web development ecosystem.