How to Use the DISQO MCP in Mastra AI

Q: How do I check DISQO metadata with Mastra AI?

Create a pre-step in your workflow that calls getplatformmetadata. This ensures your agent has the necessary permissions and quota before running long research tasks.

Automate research workflows in Mastra AI with conditional logic and reliable error handling for DISQO.

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Connect DISQO MCP to Mastra AI

Create your Vinkius account to connect DISQO 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 DISQO with Mastra AI

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Automated Research Pipelines in Mastra AI

Build agent workflows that trigger `list_insight_projects` and automatically branch based on project status. If a project is stalled, your Mastra AI agent can notify an admin or retry the fetch. This removes manual oversight from your research operations. You define the workflow once and let the engine handle the execution and retries.

Conditional Behavioral Audits for Mastra AI

Use `quick_behavioral_audit` inside your agents to decide whether to trigger deeper analysis. If the audit returns a specific threshold, your Mastra AI workflow proceeds to pull detailed consumer data. This prevents wasting API calls on stagnant panels. You keep your research costs down by only diving deep when the initial scan shows movement.

Audience Management in Mastra AI

Deploy agents to manage `list_research_audiences` and `list_largest_research_panels` for your targeting needs. Your Mastra AI agent identifies the best segments for your study and updates your records. This ensures your research always targets the right group. You can script the entire selection process to happen in the background.

Setup guide

Set up DISQO 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 DISQO 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: "disqo-mcp-client",
  servers: {
    "disqo-mcp": {
      url: new URL(
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
      ),
    },
  },
});

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

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

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by DISQO. 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 DISQO MCP in Mastra AI

Add the MCP client to your agent setup and map the DISQO tools to your workflow steps. Mastra AI will handle the connection and execute tools as needed.

You can enable tool approval for any DISQO call in your Mastra AI agent. This pauses the workflow until a human confirms the action, such as launching a new project.

Mastra AI includes built-in retry logic with exponential backoff. You configure this for your DISQO tools to ensure reliable data retrieval even during network jitter.

Create a pre-step in your workflow that calls `get_platform_metadata`. This ensures your agent has the necessary permissions and quota before running long research tasks.

The server transmits only non-PII behavioral and project data. Your Mastra AI environment processes these insights within your defined security boundaries.

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