How to Use the Pando MCP in Mastra AI

Q: What Pando data does Mastra AI need for routing?

You will need to fetch locations with listlocations and routes with listroutes. These provide the foundation for your agent's decision logic.

Build resilient logistics workflows with Mastra AI and the Pando MCP Server.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers — Included with Plan

Connect Pando MCP to Mastra AI

Create your Vinkius account to connect Pando to Mastra AI — we handle the hosting, security, and runtime updates so you don't have to. No server setup required.

GDPR Included with Plan

Setup Pando with Mastra AI

Ask AI about this MCP

ChatGPT

Claude

Perplexity Vinkius runs on Gemini

Gemini

Grok

Automated freight workflows for Mastra AI

Create reliable dispatch chains using `create_indent` and `list_carriers`. You can build logic that retries failed shipments automatically. It removes the need for manual oversight. Your agents handle the entire indent lifecycle based on the rules you set in your workflow.

Reliable carrier selection using Pando MCP

Use `list_carriers` and `list_vehicles` to find the right partner for every route. You define the criteria, and the agent picks the best match. This ensures your freight moves on time. You avoid the guesswork by letting the agent filter results based on real-time Pando data.

Handling logistics failures with Mastra AI

Use `get_indent_details` to verify state after an error occurs. You can trigger conditional branches to notify admins when a shipment stalls. It keeps your operations moving. The system detects issues early and executes your recovery plan without manual intervention.

Setup guide

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

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

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

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Pando. 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.