How to Use the CaptivateIQ MCP in Vercel AI SDK

Q: Can I list commission inquiries using CaptivateIQ and Vercel AI SDK?

Yes. Use the listcommissioninquiries tool to fetch pending disputes. Your agent can then summarize these directly in your chat interface.

Q: How do I filter commission payouts?

Call listcommissionpayouts and process the returned array in your application logic. You can filter by employee or date range before updating the UI state.

Stream commission data straight into your Vercel AI SDK frontends. Stop waiting for spinners and show payouts in real-time.

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Connect CaptivateIQ MCP to Vercel AI SDK

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

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Live commission tracking for Vercel AI SDK

Feed your UI raw commission data instantly. Use `list_commission_payouts` to push processed numbers directly into your React components without the usual round-trip delay. Your users see the numbers populate as the agent works. It turns static dashboards into live, reactive interfaces for your sales team.

Verify employee plans in the browser

Pull plan designations and details on demand using `list_employees` or `get_employee_details`. The data lands in your state management layer the moment the agent finishes its task. This keeps your frontend synced with the backend source of truth. No more stale plan information in your user-facing UI.

Manage compensation workbooks with this MCP Server

Browse active calculation environments using `list_workbooks` and `list_worksheets`. You gain full visibility into the structures behind every payout statement. Developers can now map these structures to UI elements with ease. It makes building complex financial reporting tools for your end users significantly faster.

Setup guide

Set up CaptivateIQ 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 CaptivateIQ 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 CaptivateIQ 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 CaptivateIQ. 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.

Why Choose Vinkius

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Common questions about CaptivateIQ MCP in Vercel AI SDK

Install the MCP package and initialize the client with your endpoint. Pass the tools from this MCP Server into your streamText call to let your frontend render the output.

Yes. Use the `list_commission_inquiries` tool to fetch pending disputes. Your agent can then summarize these directly in your chat interface.

It does. The HTTP transport is built for low-latency environments like edge functions. You get the speed required for production-grade financial apps.

Call `list_commission_payouts` and process the returned array in your application logic. You can filter by employee or date range before updating the UI state.

Vinkius handles your security with an ephemeral sandbox. Your sensitive compensation records are encrypted in transit and never stored on our servers after the session ends.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

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