How to Use the Microsoft Ads MCP in Vercel AI SDK

Q: Can Vercel AI SDK display Microsoft Ads budget data?

Yes, it can. By invoking listmsbudgets, your application receives the current budget allocations and can display them dynamically in your frontend components.

Stream Microsoft Ads data directly into your Vercel AI SDK interface. Build real-time dashboards where insights appear as the agent works.

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Connect Microsoft Ads MCP to Vercel AI SDK

Create your Vinkius account to connect Microsoft Ads 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 Microsoft Ads with Vercel AI SDK

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Real-time campaign monitoring in Vercel AI SDK

Feed your UI live performance data by calling `list_ms_campaigns` directly from your Edge Functions. Your application renders the results as they arrive, eliminating the need for stale static reports. This MCP Server handles the connection logic, so your frontend code focuses on display. You simply pass the tool output to your UI components to show active spend and performance metrics instantly.

Targeting audit within Vercel AI SDK workflows

Inspect audience reach and keyword effectiveness by hooking `list_ms_targeting_settings` into your generation loop. Your AI client pulls precise demographic data to explain why a specific audience segment is underperforming. Seeing these details in your interface helps you make adjustments without switching tabs. You get the raw data you need to validate your current strategy against active market conditions.

Budget management for Vercel AI SDK apps

Check current spending limits with `list_ms_budgets` to keep your ad delivery within bounds. Your agent monitors these numbers and updates the screen whenever a budget threshold is approached. This keeps the financial health of your campaigns visible to the user at all times. It turns your dashboard into an active control room for your advertising spend.

Setup guide

Set up Microsoft Ads 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 Microsoft Ads 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 Microsoft Ads transactions",
});

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

Get your connection token →

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Common questions about Microsoft Ads MCP in Vercel AI SDK

You initialize the connection using the Vercel AI SDK MCP transport. Once you define the endpoint, you pass the available tools into your streamText or generateText function calls.

Yes, it can. By invoking `list_ms_budgets`, your application receives the current budget allocations and can display them dynamically in your frontend components.

Your data remains private because the server acts as a bridge that only transmits requested information. It processes your account identifiers and campaign details locally within your authenticated session.

It provides the latest data available from the API whenever your agent triggers a tool. You control the frequency of updates through your agent's execution logic.

The server uses standard OAuth2 flows to manage your access tokens. You configure your environment variables, and the server handles the secure token refresh process automatically.

Use it with your favorite AI tools

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