How to Use the Contentsquare MCP in Mastra AI

Q: How do I add Contentsquare tools to a Mastra AI agent?

Instantiate MCPClient with your Vinkius server URL and call listTools to retrieve the toolset. You then spread these tools directly into your agent definition so it can execute tools like getmetrics on demand.

Q: How does Mastra AI use Contentsquare session enrichment?

The agent triggers enrichsession to attach offline attributes directly to session arrays. Mastra AI coordinates this step conditionally, running it only when specific CRM logs match active visitor profiles.

Build resilient Mastra AI workflows that automatically pull, enrich, and export Contentsquare UX analytics.

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Connect Contentsquare MCP to Mastra AI

Create your Vinkius account to connect Contentsquare 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 Contentsquare with Mastra AI

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Enrich session logs using Mastra AI

The `enrich_session` tool binds native JSON payloads directly to live session arrays inside your automated workflows. Your Mastra AI agent uses this tool to append headless offline attributes, like CRM logs, whenever a user session meets specific behavioral triggers. If the enrichment step fails due to network issues, Mastra's workflow engine retries with exponential backoff. It's a clean way to keep your Contentsquare session logs updated without manual babysitting.

Automate export jobs with this MCP Server

The `create_export_job` tool starts raw data pipeline chunk routing as an asynchronous background step in your workflow. Your Mastra AI client manages this by calling `get_export_job` at scheduled intervals to check the extraction execution state. You register the server URL in your `MCPClient` configuration and spread the tools returned from `listTools` into your agent. The workflow handles conditional branching, routing failed export jobs to an alert system while successfully processed logs trigger downstream analytics.

Audit URL mappings and tracking zones

The `list_mappings` tool discovers the routing trees structuring your URL paths so your agent can verify tracking coverage. Mastra AI runs this as a periodic audit step, comparing active routes against actual interaction arrays returned by `list_zonings`. When the agent detects click tracking constraints on a specific page, it automatically triggers a workflow branch to notify your product team. This turns static Contentsquare tracking data into an active, self-healing monitoring system.

Setup guide

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

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

const result = await agent.generate(
  "List recent Contentsquare 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 Contentsquare. 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 Contentsquare MCP in Mastra AI

Instantiate `MCPClient` with your Vinkius server URL and call `listTools` to retrieve the toolset. You then spread these tools directly into your agent definition so it can execute tools like `get_metrics` on demand.

Yes, Mastra's built-in workflow engine handles this MCP Server natively. If `create_export_job` fails, the system uses exponential backoff to retry the request, ensuring raw data pipeline chunks are routed reliably.

The agent triggers `enrich_session` to attach offline attributes directly to session arrays. Mastra AI coordinates this step conditionally, running it only when specific CRM logs match active visitor profiles.

The client auto-detects the transport layer, relying on either SSE or Streamable HTTP depending on your Vinkius network configuration. You do not need to configure transport protocols manually.

All requests transit through Vinkius's zero-trust gateway using a single endpoint token. Your raw session arrays and CRM payloads are processed in ephemeral V8 isolates, preventing any persistent storage or exposure of sensitive UX logs.

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