How to Use the Measured MCP in Mastra AI

Q: How do I register the Measured tools inside my Mastra AI agent config?

Instantiate the client, call listTools(), and spread them into your agent's tool array. The agent can then call getinsights or listchannels as needed during workflow execution.

Q: How does Mastra AI handle human-in-the-loop approvals for marketing reports?

Set requireToolApproval to true when configuring your agent. When the agent attempts to fetch sensitive data via listreports, the workflow pauses until you approve the action.

Q: Is my marketing performance data safe when using Mastra AI with this server?

Yes. Your raw ROAS metrics and channel data fetched via getperformancebychannel pass through an ephemeral, zero-trust V8 sandbox using the Vinkius MCP gateway. Your credentials are never stored in plain text or shared with external model hosts.

Build automated marketing workflows that fetch Measured incrementality metrics using Mastra AI agents.

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Connect Measured MCP to Mastra AI

Create your Vinkius account to connect Measured 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 Measured with Mastra AI

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Automated ROAS Monitoring with Mastra AI Workflows

This Mastra AI integration relies on `get_performance_summary` to monitor daily ROAS thresholds via an MCP connection. If performance drops below your target, the workflow engine triggers conditional branches to isolate the failing marketing channel. The agent then runs `get_performance_by_channel` to pinpoint the exact source of the drop. Mastra AI manages the retry logic automatically, so you don't have to worry about temporary API timeouts.

Multi-Step Incrementality Audits

Use the `get_incrementality_scores` tool within a Mastra AI workflow to audit your active marketing channels. The agent compares these scores against raw performance data to find over-attributed ad spend. By calling `list_integrations` during the audit, the workflow checks which platforms are actively sending data. Mastra AI handles the state machine, pausing for human approval if the agent suggests pausing a channel.

Error-Resilient Campaign Reporting

This MCP Server exposes `list_reports` to let your Mastra AI agent fetch scheduled performance documents. If the platform is slow to respond, Mastra's built-in exponential backoff handles the delay without crashing your workflow. Once the report is ready, the agent calls `get_campaign_performance` to extract the final metrics. The workflow then formats the data and sends it to your team, ensuring consistent reporting even during API spikes.

Setup guide

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

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

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

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Common questions about Measured MCP in Mastra AI

Mastra AI has built-in retry mechanisms with exponential backoff. If `get_campaign_performance` hits a rate limit, the framework automatically retries the call until the data is fetched.

No, this MCP Server only supports read actions. Your agent can use `get_incrementality_scores` to analyze performance, but you must route the output to an external tool to execute budget changes.

Instantiate the client, call `listTools()`, and spread them into your agent's tool array. The agent can then call `get_insights` or `list_channels` as needed during workflow execution.

Set `requireToolApproval` to true when configuring your agent. When the agent attempts to fetch sensitive data via `list_reports`, the workflow pauses until you approve the action.

Yes. Your raw ROAS metrics and channel data fetched via `get_performance_by_channel` pass through an ephemeral, zero-trust V8 sandbox using the Vinkius MCP gateway. Your credentials are never stored in plain text or shared with external model hosts.

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