How to Use the NinjaCat MCP in Vercel AI SDK

Q: How does the UI render NinjaCat report histories using the Vercel AI SDK?

You use streamText to pipe getreporthistory directly into your UI. The Vercel AI SDK reads the incoming tool execution history and updates your React state in real-time.

Build Next.js apps that stream live NinjaCat marketing reports directly to your users using the Vercel AI SDK.

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Connect NinjaCat MCP to Vercel AI SDK

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

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Live Client Performance Feeds

`list_agency_campaigns` pulls active marketing campaigns from NinjaCat directly into your Vercel AI SDK stream. This specific NinjaCat tool lets your React components render real-time campaign lists inside your Vercel AI SDK interface without waiting for full payloads. Your Vercel AI SDK frontend parses the NinjaCat campaign JSON payload on the fly. By passing this NinjaCat tool to your streamText function, you build Vercel AI SDK dashboards where clients watch their live marketing metrics populate cell by cell.

Real-Time Report Downloads via MCP Server

`get_report_download_url` generates direct download links for your NinjaCat PDF reports. Instead of making Vercel AI SDK users wait, this NinjaCat MCP Server tool injects the download link into your chat UI the millisecond it is ready. You configure the Vercel AI SDK transport using HTTP to keep your NinjaCat data fetches lightweight. The Vercel AI SDK processes this NinjaCat response instantly, giving your users immediate file access.

Instant Advertiser Diagnostics

`get_advertiser` fetches profile details for any specific marketer in your NinjaCat system. This NinjaCat MCP Server tool feeds clean metadata into your streaming Vercel AI SDK components so account managers can verify account health. Because you use the Vercel AI SDK, you can map these NinjaCat tool outputs to custom React primitives. Your Vercel AI SDK interface updates instantly, showing NinjaCat billing details and status updates without lagging.

Setup guide

Set up NinjaCat 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 NinjaCat 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 NinjaCat 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 NinjaCat. 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 NinjaCat MCP in Vercel AI SDK

You pass your endpoint token via the authProvider option when configuring your MCP client. This keeps your credentials secure on the server side while streaming data to your Next.js frontend.

Yes, you can. The MCP client uses standard HTTP transports, which run perfectly inside the Vercel AI SDK Edge runtime without cold-start delays.

You use streamText to pipe `get_report_history` directly into your UI. The Vercel AI SDK reads the incoming tool execution history and updates your React state in real-time.

Your code should wrap the mcpClient.tools() call in a standard promise timeout. If the connection drops, your UI can gracefully fallback to cached data.

Every request runs in an isolated V8 sandbox that destroys itself immediately after execution. Your marketing reports and advertiser accounts are never cached or stored on our servers.

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