How to Use the TransportAPI MCP in Mastra AI

Q: What kind of failures can Mastra AI handle with TransportAPI?

It excels at handling multi-step failures. For example, if getraildepartures is unavailable, the workflow doesn't crash; it executes a fallback path to check bus services instead.

Q: Can Mastra AI plan trips across different modes?

Yes. The getjourneyplan tool supports multimodal trips combining buses, rail, tram, and walking. Your workflow can reliably use this function to build a full itinerary.

Q: How do I use TransportAPI with Mastra AI for checking services?

You can build a workflow that first checks getupdates for general disruptions, then uses the resulting line names to call specific tools like getbusarrivals or getraildepartures, ensuring all data points are verified before output.

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Perplexity

Manage complex transit planning

When a user needs door-to-door directions, you call `get_journey_plan`. This is crucial because the workflow must handle failures—maybe one leg is canceled. Your Mastra AI agent can retry the plan or notify an admin if the initial route fails. The MCP Server provides all necessary inputs: bus lines, rail connections, and walking paths to build a complete itinerary.

Handle service disruptions automatically

Disruption management requires reliability. Use `get_updates` in your workflow engine. If the first line checked is disrupted, the agent can automatically branch and check alternative routes using `get_rail_services` instead. This ability to conditionally switch between checking bus, rail, or tram status makes your complex workflows highly robust.

Monitor station and stop details

For building accurate user profiles, you need detailed location data. Use `get_station_info` for comprehensive metadata about a UK rail station (like facilities or accessibility). You can also use `get_stop_info` to get specifics on bus stops. The Mastra AI platform makes sure that even if the facility check fails once, your workflow continues and records the error for later review.

Setup guide

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

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

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

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Common questions about TransportAPI MCP in Mastra AI

Mastra AI treats the MCP Server like a reliable tool in a complex chain. Your agent calls specific tools, like `get_rail_arrivals`, and if that call fails due to rate limiting or data issues, your workflow engine handles the retry automatically.

It excels at handling multi-step failures. For example, if `get_rail_departures` is unavailable, the workflow doesn't crash; it executes a fallback path to check bus services instead.

Yes. The `get_journey_plan` tool supports multimodal trips combining buses, rail, tram, and walking. Your workflow can reliably use this function to build a full itinerary.

The server touches vast amounts of transit operational data: schedules, real-time times, station metadata, service disruption alerts, and detailed bus stop information. The exact data type includes comprehensive facility metadata.

You can build a workflow that first checks `get_updates` for general disruptions, then uses the resulting line names to call specific tools like `get_bus_arrivals` or `get_rail_departures`, ensuring all data points are verified before output.

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