How to Use the Gingr MCP in Mastra AI

Q: How does Mastra AI handle human approval for Gingr tools?

You set requireToolApproval in your agent definition. This forces the system to pause until you explicitly confirm the action, ensuring safety for all pet-related tasks.

Q: Can I branch my workflow based on Gingr owner data?

Absolutely. You can use the output of searchownercustomfields to create conditional logic branches within your Mastra AI agents.

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Connect Gingr MCP to Mastra AI

Create your Vinkius account to connect Gingr 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 Gingr with Mastra AI

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Perplexity

Automate owner communication in Mastra AI

Trigger multi-step sequences when a booking changes. You can use `get_pet_owner_details` to fetch contact info and pass it to your notification agents automatically. It handles the logic flow without you needing to manually verify every step. If a reservation is updated, the agent knows exactly who to contact.

Sync your digital whiteboard with Mastra AI

Use `get_digital_whiteboard` to feed current kennel status into your workflow engine. It allows your agents to make decisions based on real-time room occupancy. Your agents can detect conflicts before they happen. They flag issues, allowing you to intervene only when a human touch is required.

Search custom fields with Mastra AI agents

Run `search_pet_custom_fields` to find specific medical or behavioral notes. Your agents use this data to modify their behavior based on the specific needs of the animal. It keeps your agents context-aware. They stop making generic assumptions and start acting on the actual data stored in your system.

Setup guide

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

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

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

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Common questions about Gingr MCP in Mastra AI

Yes. Mastra AI has a built-in workflow engine that manages retries and backoff logic if an API call to the server times out.

You set `requireToolApproval` in your agent definition. This forces the system to pause until you explicitly confirm the action, ensuring safety for all pet-related tasks.

The server is stateless and ephemeral. Every request is verified via `verify_api_connection`, keeping your workflow clean and avoiding stale data.

Absolutely. You can use the output of `search_owner_custom_fields` to create conditional logic branches within your Mastra AI agents.

We keep the scope limited to specific tools. The server only accesses pet health and owner contact records when your agent explicitly invokes the relevant tool.

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