How to Use the TransportAPI MCP in Mastra AI

Q: Can I build multi-step journeys using TransportAPI Alternative MCP Server with Mastra AI?

Yes. You sequence tools like gettransportbypostcode followed by planpublictransportjourney. If the journey fails, your workflow can automatically notify an administrator.

Q: What if I need to check both bus and train services with TransportAPI Alternative MCP Server in Mastra AI?

You set up a branching path. One branch uses getlivebusdepartures, while the other executes getlivetraindepartures. The agent decides which path to take based on user input.

Build failure-proof transit logic with Mastra AI and TransportAPI Alternative MCP Server.

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Setup TransportAPI with Mastra AI

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Complex Trip Planning Workflows

Building a trip planner? Use `plan_public_transport_journey` as the first step in your workflow. If the initial plan fails (say, due to service disruption), Mastra AI can automatically retry with exponential backoff or use an alternative tool like `get_train_station_timetable`. This conditional branching handles real-world transit failures gracefully, notifying the admin if retries fail.

Real-Time Status Checks

Want to check live departures? Trigger `get_live_bus_departures` or `get_live_train_departures`. If the service is down, the workflow can catch that failure and switch to checking static schedules using `get_bus_service` instead. This robust handling of different data sources makes your agent reliable.

Multi-Step Location Searches

A user might ask 'How do I get from my address to the station?' Start by calling `get_transport_by_postcode` to find the nearest hub. Then, use that result as input for `search_transport_places` to refine the location. This chain of events ensures all necessary data points are gathered before proceeding with fare calculation via `get_train_fares`.

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-alternative-mcp-client",
  servers: {
    "transportapi-alternative-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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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by TransportAPI. 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.

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Common questions about TransportAPI MCP in Mastra AI

Mastra AI manages failure through automatic retries and conditional logic. If the initial tool call fails, it can execute a fallback plan—for instance, switching from live data to scheduled timetables.

Yes. You sequence tools like `get_transport_by_postcode` followed by `plan_public_transport_journey`. If the journey fails, your workflow can automatically notify an administrator.

You set up a branching path. One branch uses `get_live_bus_departures`, while the other executes `get_live_train_departures`. The agent decides which path to take based on user input.

It does. You can set up a workflow that takes coordinates, calls `get_nearby_bus_stops`, and then continues processing the list of found locations.

This server deals with public transit schedules, route timetables, coordinates (GPS), station names, and fare pricing. It only uses publicly available travel information.

Use it with your favorite AI tools

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