How to Use the Zinrelo MCP in Mastra AI

Q: How do I ensure point deductions work with Zinrelo and Mastra AI?

Set up a dedicated workflow step calling deductpoints. Use the built-in retries to guarantee that even if the initial API call fails, the deduction will eventually process.

Q: Can I automate member enrollment with Zinrelo and Mastra AI?

Yes. You can write a dedicated step using enrollmember in your agent's sequence. This ensures that every time a new user signs up, their record is created correctly.

Q: How do I retrieve member details using Zinrelo and Mastra AI?

Start your workflow with getmemberdetails to pull the necessary profile information for a specific user. This data then feeds into subsequent steps, like checking their points balance.

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Connect Zinrelo MCP to Mastra AI

Create your Vinkius account to connect Zinrelo 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 Zinrelo with Mastra AI

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Process Purchases and Points

You can build a multi-step workflow that first calls `award_points_purchase` upon success. If the points award fails, your agent framework can automatically retry or notify an admin. The system also supports dedicating specific actions using `deduct_points`, which is great for handling reversals after a failed process.

Handle Member Status and Rewards

`enroll_member` is perfect for initial sign-ups. You can set up branching logic: if the member record already exists, don't re-create it; just call `get_member_details` to confirm. The workflow also incorporates reward redemption by executing `redeem_reward`, ensuring the transaction completes correctly or triggers a failure path.

Audit and Track Member Activity

Need to audit what happened? Use `list_member_transactions` within your Mastra AI workflow. This gives you the full history, which is critical for compliance. For broad checks, `list_loyalty_members` provides the necessary scope to pull data on multiple users at once.

Setup guide

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

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

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

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Common questions about Zinrelo MCP in Mastra AI

Set up a dedicated workflow step calling `deduct_points`. Use the built-in retries to guarantee that even if the initial API call fails, the deduction will eventually process.

The MCP Server touches loyalty member details and transaction history. It manages points data (purchase awards, deductions) across the workflow execution.

Yes. You can write a dedicated step using `enroll_member` in your agent's sequence. This ensures that every time a new user signs up, their record is created correctly.

The framework supports complex sequences like awarding points (`award_points_activity`) followed by listing those transactions. The workflow handles the dependencies between these calls gracefully.

Start your workflow with `get_member_details` to pull the necessary profile information for a specific user. This data then feeds into subsequent steps, like checking their points balance.

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