How to Use the LA Metro MCP in Mastra AI

Q: How do I map rail stations using Mastra AI and this LA Metro integration?

You call getrailstations to fetch the complete list of station IDs and geographic coordinates. Your Mastra AI agent then stores this metadata to resolve station names in subsequent journey queries.

Q: Does this integration support multi-step route planning?

Yes. The getrailtorail tool calculates complete rail journeys. Your agent can run this tool first, then verify actual train positions using getrailvehiclepositions to ensure the recommended trains are running.

Build resilient, self-healing transit workflows with Mastra AI and live LA Metro vehicle telemetry.

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Connect LA Metro MCP to Mastra AI

Create your Vinkius account to connect LA Metro 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 LA Metro with Mastra AI

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Automate Transit Dispatch Alerts with Mastra AI

The `get_service_alerts` tool exposes active system disruptions so your Mastra AI agents can trigger alternative routing workflows instantly. If a major delay hits the Blue Line, your workflow automatically recalculates options. You can chain this with `get_rail_to_rail` to find alternative tracks without writing complex conditional routing code yourself. Mastra handles the retries and branching if the API rate limits act up.

Track Active Bus Fleets with Mastra Workflows

The `get_bus_vehicles` tool feeds real-time bus coordinates and run IDs directly into your Mastra AI agent loops using this MCP connection. This lets you build automated monitors that track specific high-traffic routes like the 720 Rapid. Because Mastra supports automatic retries, temporary GPS dropouts in the LA Metro API won't break your tracking loops. The agent simply backs off and retries `get_bus_locations` until the connection stabilizes.

Build Commuter Prediction Pipelines

The `get_stop_predictions` tool fetches immediate arrival estimates for any bus stop in the county. Your Mastra AI workflows can poll this endpoint to send push notifications to commuters exactly five minutes before their bus arrives. Combining this with `get_bus_schedule` allows your agent to compare scheduled times against actual real-time positions. You get a clear picture of overall route performance without manual data scraping via our MCP Server.

Setup guide

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

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

const result = await agent.generate(
  "List recent LA Metro 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 LA Metro. 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 LA Metro MCP in Mastra AI

Mastra AI uses its built-in workflow engine to queue requests and apply exponential backoff. When querying high-frequency tools like `get_bus_locations`, the system prevents API bans by spacing out the calls.

Yes. You can configure a Mastra AI agent to run a background loop calling `get_service_alerts`. If a severe disruption is detected, the workflow triggers your notification system.

You call `get_rail_stations` to fetch the complete list of station IDs and geographic coordinates. Your Mastra AI agent then stores this metadata to resolve station names in subsequent journey queries.

Yes. The `get_rail_to_rail` tool calculates complete rail journeys. Your agent can run this tool first, then verify actual train positions using `get_rail_vehicle_positions` to ensure the recommended trains are running.

This server only handles public transit data, such as vehicle IDs and station coordinates. Vinkius secures the connection by executing the code in a zero-trust environment, protecting your transit queries from exposure.

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