How to Use the AdButler MCP in Vercel AI SDK

Q: How do I connect AdButler to the Vercel AI SDK?

Run npm install ai @ai-sdk/mcp in your project. Call createMCPClient with the Vinkius endpoint URL and pass the resulting tools into your generation function.

Q: Can the Vercel AI SDK fetch AdButler performance reports?

Yes, the agent calls getperformancereport to pull aggregated CTR and impressions. You define the date ranges in the prompt, and the SDK streams the resulting metrics back.

Q: How do I map AdButler zones using Vercel AI SDK?

Your agent will first execute listpublishers to get network IDs. It immediately feeds those results into listzones to resolve the actual ad placements.

Build custom ad reporting dashboards that stream AdButler metrics straight to your Next.js frontend using the Vercel AI SDK.

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Connect AdButler MCP to Vercel AI SDK

Create your Vinkius account to connect AdButler 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 AdButler with Vercel AI SDK

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Stream Ad Performance to React

`get_performance_report` pulls your ad impressions, clicks, and CTR directly from the AdButler MCP Server. Your Vercel AI SDK backend pipes this data into a live React component as it arrives. Users watch their campaign stats render instantly instead of staring at a spinning loader. Passing specific dates filters the aggregation. The edge function handles the HTTP transport setup and closes the connection on completion. Next.js natively handles the UI state updates.

Map Publishers and Zones in UI

`list_publishers` fetches the network of partners managing your ad inventory. You pass those IDs right back into `list_zones` to map out active placements. The client renders interactive dropdowns populated with real-time zone data. Fetching nested data through an LLM usually feels slow. Streaming the tool calls with `streamText` breaks that latency barrier. Developers get a snappy interface for matching self-serve ads to specific publisher slots.

Audit Campaigns via Vercel AI SDK

`list_campaigns` grabs active and pending self-serve orders from your account. Combining this with `list_creatives` lets the agent match banners and videos to their target campaigns. The entire catalog streams down to your Svelte or Vue frontend. Building this without an MCP integration requires writing custom pagination and auth logic. Passing `mcpClient.tools()` to your generation function skips the boilerplate entirely. Your users just ask for the pending ads and see the assets appear on screen.

Setup guide

Set up AdButler 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 AdButler 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 AdButler transactions",
});

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

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by AdButler. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about AdButler MCP in Vercel AI SDK

Run `npm install ai @ai-sdk/mcp` in your project. Call `createMCPClient` with the Vinkius endpoint URL and pass the resulting tools into your generation function.

Yes, the agent calls `get_performance_report` to pull aggregated CTR and impressions. You define the date ranges in the prompt, and the SDK streams the resulting metrics back.

The HTTP transport runs natively in Vercel Edge Functions. Just remember to close the client after your streaming text function completes.

Your agent will first execute `list_publishers` to get network IDs. It immediately feeds those results into `list_zones` to resolve the actual ad placements.

Your CTR and impression data passes strictly between the API and your edge function. Vinkius hosts this MCP tool in an ephemeral V8 Isolate Sandbox. Nothing gets stored after the session ends.

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