How to Use the Vercel MCP in Vercel AI SDK

Q: How do I check Vercel deployments using the Vercel AI SDK?

Use the listdeployments tool to get a history of builds for your project. The streaming nature of the Vercel AI SDK lets you show this list immediately, avoiding loading spinners.

Q: Is listing projects safe when using Vercel and the ai-sdk?

Yes. The listprojects tool only reads metadata about your account's deployments. It doesn't expose any sensitive keys or private content, just the project names.

Q: Can I see all my Vercel domains with the ai-sdk?

You can use listaccountdomains to get a list of high-level apex domains managed by your account. This helps ensure your AI client knows the full scope of connected services.

Q: What if I need to cancel a build using the Vercel AI SDK on Vercel?

The cancelactivebuild tool lets you abort any running compilation pipeline. This gives you instant control over resources, preventing unnecessary builds from consuming time or bandwidth.

Control your full Vercel deployment stack from your Next.js frontend using the Vercel AI SDK.

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Connect Vercel MCP to Vercel AI SDK

Create your Vinkius account to connect Vercel to Vercel AI SDK and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup Vercel with Vercel AI SDK

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Getting Project Details with MCP Server

The `get_project_details` tool fetches all configuration data for a specific project. This lets your AI client read the setup, including associated frameworks and aliases. You get the necessary context to display full deployment information in real time on the UI.

Triggering Builds with Vercel AI SDK

When you call `trigger_github_deployment`, your agent initiates a new build for the project using a specific Git reference. This is perfect for user-initiated actions. The client can immediately stream the status of that build, showing the end user exactly what's happening.

Listing Project Status

The `list_deployments` tool pulls a list of recent CI/CD builds for any given project. Your agent can iterate through these build records to determine the last successful deployment time, letting your frontend display live status updates.

Setup guide

Set up Vercel MCP in Vercel AI SDK

Prerequisites

Node.js 18+ and a TypeScript project
ai + @modelcontextprotocol/sdk packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies

Run npm install ai @modelcontextprotocol/sdk plus your preferred model provider (e.g. @ai-sdk/openai).
2

Create the Streamable HTTP transport

Use StreamableHTTPClientTransport with your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Discover and use tools

Call mcpClient.tools() to auto-discover all Vercel tools. Pass them directly to generateText() or streamText() — no manual schema definitions needed.
4

Works with any model provider

Swap openai("gpt-4o") for any AI SDK provider — Anthropic, Google, Mistral. The MCP tools work identically across all supported models.

index.ts

import { experimental_createMCPClient as createMCPClient } from "ai";
import { StreamableHTTPClientTransport } from "@modelcontextprotocol/sdk/client/streamableHttp";
import { generateText } from "ai";
import { openai } from "@ai-sdk/openai";

const transport = new StreamableHTTPClientTransport(
  new URL("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
);

const mcpClient = await createMCPClient({ transport });
const tools = await mcpClient.tools();

const { text } = await generateText({
  model: openai("gpt-4o"),
  tools,
  prompt: "List recent Vercel transactions",
});

console.log(text);
await mcpClient.close();

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Common questions about Vercel MCP in Vercel AI SDK

Use the `list_deployments` tool to get a history of builds for your project. The streaming nature of the Vercel AI SDK lets you show this list immediately, avoiding loading spinners.

Yes. The `list_projects` tool only reads metadata about your account's deployments. It doesn't expose any sensitive keys or private content, just the project names.

You can use `list_account_domains` to get a list of high-level apex domains managed by your account. This helps ensure your AI client knows the full scope of connected services.

This server touches project configuration data, specific deployment execution details, and account domain information. It's all read-only metadata about your infrastructure.

The `cancel_active_build` tool lets you abort any running compilation pipeline. This gives you instant control over resources, preventing unnecessary builds from consuming time or bandwidth.

Use it with your favorite AI tools

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