How to Use the Mainstay (AdmitHub) MCP in Mastra AI

Q: How do we handle branching logic for Mainstay (AdmitHub) campaigns in Mastra AI?

Your Mastra AI workflow calls listcampaigns to check active initiatives. It then uses conditional steps to branch the workflow based on which campaign the student is currently enrolled in.

Q: How does this setup protect sensitive student message logs?

Every call to listmessages runs within an isolated, zero-trust MCP sandbox. Your credentials are encrypted at rest, and message data is never cached on the host.

Build automated, resilient student outreach workflows with Mastra AI and the Mainstay (AdmitHub) MCP Server.

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Connect Mainstay (AdmitHub) MCP to Mastra AI

Create your Vinkius account to connect Mainstay (AdmitHub) 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 Mainstay (AdmitHub) with Mastra AI

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Automated Campaign Nudge Workflows

This MCP Server uses `list_campaigns` to feed active student outreach programs into Mastra AI workflow engines. Your agent checks active campaigns and triggers automated follow-ups based on real student responses. Mastra's retry logic ensures that if a network glitch occurs while fetching campaigns, the system automatically backs off and retries. This keeps your automated nudges running without human intervention.

Conditional Student Routing

This tool uses `list_contacts` to retrieve student segments and apply custom branching logic. If a student's profile matches specific criteria, Mastra AI routes them to a specialized advisor queue. By querying `list_custom_fields`, the workflow engine checks custom metadata to make routing decisions. This lets you build complex logic, like sending different SMS reminders to in-state versus out-of-state students.

Message Log Auditing and Retries

This tool uses `list_messages` to audit communication history and trigger corrective actions. If a crucial SMS bounce is detected, the Mastra AI agent can automatically log the error and queue a retry. You can combine this with `get_contact_details` to verify the student's phone number before attempting another send. This prevents wasting SMS credits on dead numbers.

Setup guide

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

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

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

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Common questions about Mainstay (AdmitHub) MCP in Mastra AI

Mastra AI features a built-in workflow engine with automatic exponential backoff. If the MCP Server hits an API limit during `list_messages` calls, Mastra pauses and retries.

Yes. You can configure Mastra AI to pause the workflow when calling tools that fetch sensitive student profiles, requiring an advisor to click approve before continuing.

Your Mastra AI workflow calls `list_campaigns` to check active initiatives. It then uses conditional steps to branch the workflow based on which campaign the student is currently enrolled in.

Yes. The server is fully compatible with Mastra AI's deployment model, allowing you to run your agent workflows on any cloud provider.

Every call to `list_messages` runs within an isolated, zero-trust MCP sandbox. Your credentials are encrypted at rest, and message data is never cached on the host.

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