How to Use the Rapid URL Indexer MCP in Vercel AI SDK

Q: Can I track my Rapid URL Indexer Alternative usage inside my Vercel AI SDK app?

Yes. Call getcreditbalance within your workflow to check your remaining credits. It returns your current balance in real-time.

Q: How do I automate URL submissions using Rapid URL Indexer Alternative in my Vercel AI SDK project?

Pass submitproject to your AI client's tool list. Your agent will handle the batch delivery to the indexer automatically.

Push URLs to Google directly from your Vercel AI SDK frontend. Automate indexing and track project reports in real-time.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers — Included with Plan

Connect Rapid URL Indexer MCP to Vercel AI SDK

Create your Vinkius account to connect Rapid URL Indexer to Vercel AI SDK — we handle the hosting, security, and runtime updates so you don't have to. No server setup required.

GDPR Included with Plan

Setup Rapid URL Indexer with Vercel AI SDK

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Stream indexing results to your Vercel AI SDK UI

Feed `submit_project` outputs directly into your React or Next.js components. Stop waiting for spinners and show users exactly which URLs are hitting the indexer. Your UI updates as the MCP Server processes batches. It handles the API handshake so your frontend stays focused on rendering.

Manage your Rapid URL Indexer Alternative credits

Use `get_credit_balance` to keep your users informed about their remaining quota. Never let a production run fail because of an empty balance. Integrate this check before triggering any batch submission. You'll catch potential issues before they hit the wire.

Monitor indexing progress with Vercel AI SDK

Call `get_project_status` to pull real-time data on your active indexing jobs. Display progress bars or success counts based on the returned object. Use `get_project_report` to generate detailed summaries for your users. It feeds clean data into your state management layer.

Setup guide

Set up Rapid URL Indexer 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 Rapid URL Indexer 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 Rapid URL Indexer transactions",
});

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

Get your connection token →

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