How to Use the CaptivateIQ MCP in Mastra AI

Q: Are commission inquiries handled by CaptivateIQ in Mastra AI?

They are. You can map listcommissioninquiries to a specific agent task to monitor incoming disputes. The agent can then trigger follow-up actions if needed.

Build reliable commission workflows in Mastra AI. Automate your compensation ops with built-in retry logic and error handling.

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Connect CaptivateIQ MCP to Mastra AI

Create your Vinkius account to connect CaptivateIQ to Mastra AI 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 Mastra AI

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Automate commission logic with Mastra AI

Trigger complex payout reviews by chaining `list_commission_payouts` with your custom agent logic. If a connection drops, the workflow engine handles the retry automatically. This keeps your operational pipelines moving without manual intervention. You define the steps, and the agent executes the logic against your live data.

Handle commission inquiries systematically

Use `list_commission_inquiries` as a trigger for your agent to route disputes to the right department. You can build conditional branches to handle specific inquiry types differently. It removes the guesswork from your dispute resolution process. Every inquiry gets logged and acted upon according to your strict defined rules.

Deep integration with this MCP Server

Access your entire compensation structure by calling `list_workbooks` and `list_worksheets`. Your agents can now audit calculation health before finalizing any payouts. This gives your automation agents context that used to be hidden in spreadsheets. They act on the same data your finance team uses.

Setup guide

Set up CaptivateIQ MCP in Mastra AI

Prerequisites

Node.js 18+ and a TypeScript project
@mastra/mcp + @mastra/core packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run npm install @mastra/mcp @mastra/core plus your preferred model provider (e.g. @ai-sdk/openai).
2

Configure the MCPClient
Create an MCPClient with your Vinkius endpoint as a URL object. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Discover and inject tools
Call mcpClient.listTools() and spread the result into your agent's tools object. All CaptivateIQ tools become native Mastra tools.
4

Run with any model
Swap openai("gpt-4o") for any AI SDK-compatible provider. Call agent.generate() and the agent routes tool calls through MCP automatically.

agent.ts

import { MCPClient } from "@mastra/mcp";
import { Agent } from "@mastra/core/agent";
import { openai } from "@ai-sdk/openai";

const mcpClient = new MCPClient({
  id: "captivateiq-mcp-client",
  servers: {
    "captivateiq-mcp": {
      url: new URL(
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
      ),
    },
  },
});

const agent = new Agent({
  name: "CaptivateIQ Agent",
  model: openai("gpt-4o"),
  instructions: "You have access to CaptivateIQ tools.",
  tools: {
    ...(await mcpClient.listTools()),
  },
});

const result = await agent.generate(
  "List recent CaptivateIQ transactions"
);
console.log(result.text);

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Common questions about CaptivateIQ MCP in Mastra AI

Add the server URL to your Mastra client configuration. The framework will automatically detect and register all eight available tools for your agents.

They are. You can map `list_commission_inquiries` to a specific agent task to monitor incoming disputes. The agent can then trigger follow-up actions if needed.

You can. Since Mastra supports exponential backoff, any transient network issue during a tool call is handled without crashing your entire workflow.

Use the requireToolApproval setting to force human confirmation. This is best for sensitive actions like moving funds or updating employee designations.

We enforce strict isolation at the sandbox level. Your employee compensation figures are processed in a secure memory space that is wiped clean as soon as your workflow finishes.

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