How to Use the Campaigner MCP in Mastra AI

Build complex marketing logic in Mastra AI with Campaigner automation tools.

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Connect Campaigner MCP to Mastra AI

Create your Vinkius account to connect Campaigner 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 Campaigner with Mastra AI

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Perplexity

Mastra AI workflow integration for Campaigner

Chain `list_workflows` and `list_segments` to build conditional logic that triggers based on audience behavior. Your agent decides the next move when a segment changes. This setup handles failures automatically. If a call drops, the framework retries the operation so your marketing data remains consistent.

Automate audience segmentation in Mastra AI

Use `list_segments` to feed your agent the current audience breakdown. It can then map specific campaigns to the right groups without human oversight. This creates a loop where your agent learns which segments perform best. You just define the goal and let the workflow engine execute the commands.

Sync Campaigner subscriber growth with Mastra AI

Use `create_subscriber` inside your agent's task list to capture leads from your own workflows. It handles the data transfer behind the scenes. Your agent checks the subscriber state before pushing updates. This keeps your lists clean and prevents duplicate entries during high-volume periods.

Setup guide

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

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

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

Initialize the MCPClient in your Mastra config file with the Vinkius server URL. Once added, your agent automatically detects the available tools for your workflows.

Mastra AI includes built-in retry logic for every tool call. If a Campaigner request fails, the agent handles the backoff and attempts the operation again.

It does. You can set requireToolApproval to true for any Campaigner action, forcing the agent to wait for your manual sign-off.

All traffic between your agent and the server is encrypted. We use an ephemeral sandbox to ensure your marketing data isn't exposed to other processes.

Your subscriber data is treated as sensitive input. The server only processes the specific records requested by your agent and clears the context after the task ends.

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