How to Use the Lyko MCP in Vercel AI SDK

Q: How do I register the Lyko MCP Server tools inside a Vercel AI SDK project?

Install @ai-sdk/mcp and initialize the client using createMCPClient. You then pass mcpClient.tools() directly into the tools parameter of generateText or streamText to access Lyko transit endpoints. Remember to call mcpClient.close() once the streaming session completes to prevent memory leaks.

Q: How does Vercel AI SDK handle live transit updates from Lyko without UI lag?

The SDK uses UI streaming to render components as soon as getarrivals or getdepartures yields data. This means your Vercel AI SDK interface displays the train platform and ETA numbers incrementally instead of waiting for the entire Lyko payload to resolve.

Stream real-time Lyko transit bookings and route calculations directly into React components using Vercel AI SDK.

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Connect Lyko MCP to Vercel AI SDK

Create your Vinkius account to connect Lyko to Vercel AI SDK 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 Lyko with Vercel AI SDK

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Stream transit boards with Vercel AI SDK

`get_departures` and `get_arrivals` feed raw station schedules directly into your Vercel AI SDK frontend stream. This setup bypasses the usual loading spinners by rendering live train and bus times the exact millisecond the Lyko API responds. Your React components render incoming Lyko transit data block-by-block as the AI processes the schedule. Users watch platform numbers and delay indicators populate in real-time instead of staring at a blank UI.

Multi-modal route mapping inside edge functions

`plan_trip` combines trains, buses, and local bike-sharing systems into a single itinerary payload that runs inside lightweight Vercel AI SDK edge environments. Running this MCP Server on the edge keeps your API latency under 100ms while generating complex travel paths. Your AI client parses the Lyko coordinates, maps out the walking transfers, and builds a clean UI representation. Because the server runs in a V8 sandbox, you execute these heavy routing calculations close to your users.

Instant ticket booking from streaming chat

`book_trip` handles mobility reservations, ticket purchases, and QR code generation directly within your conversational Vercel AI SDK interface using this MCP Server. When your user confirms a train route, the tool executes the transaction and immediately streams the confirmation payload. The Vercel AI SDK client processes the reservation details and updates the user's view with active ticket states. You avoid page redirects by handling the entire Lyko booking lifecycle inside a single streaming session.

Setup guide

Set up Lyko MCP in Vercel AI SDK

Prerequisites

Node.js 18+ and a TypeScript project
ai + @modelcontextprotocol/sdk packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies

Run npm install ai @modelcontextprotocol/sdk plus your preferred model provider (e.g. @ai-sdk/openai).
2

Create the Streamable HTTP transport

Use StreamableHTTPClientTransport with your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Discover and use tools

Call mcpClient.tools() to auto-discover all Lyko tools. Pass them directly to generateText() or streamText() — no manual schema definitions needed.
4

Works with any model provider

Swap openai("gpt-4o") for any AI SDK provider — Anthropic, Google, Mistral. The MCP tools work identically across all supported models.

index.ts

import { experimental_createMCPClient as createMCPClient } from "ai";
import { StreamableHTTPClientTransport } from "@modelcontextprotocol/sdk/client/streamableHttp";
import { generateText } from "ai";
import { openai } from "@ai-sdk/openai";

const transport = new StreamableHTTPClientTransport(
  new URL("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
);

const mcpClient = await createMCPClient({ transport });
const tools = await mcpClient.tools();

const { text } = await generateText({
  model: openai("gpt-4o"),
  tools,
  prompt: "List recent Lyko transactions",
});

console.log(text);
await mcpClient.close();

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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 Lyko. 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 Lyko MCP in Vercel AI SDK

Install `@ai-sdk/mcp` and initialize the client using `createMCPClient`. You then pass `mcpClient.tools()` directly into the `tools` parameter of `generateText` or `streamText` to access Lyko transit endpoints. Remember to call `mcpClient.close()` once the streaming session completes to prevent memory leaks.

Yes, the server is fully compatible with edge environments. Your Vercel AI SDK edge functions call `plan_trip` to pull real-time routes and stream the JSON chunks directly to your React frontend. This setup keeps your cold starts near zero.

The SDK uses UI streaming to render components as soon as `get_arrivals` or `get_departures` yields data. This means your Vercel AI SDK interface displays the train platform and ETA numbers incrementally instead of waiting for the entire Lyko payload to resolve.

Your interface displays active delay indicators immediately. The `get_network_status` tool retrieves active service alerts, which Vercel AI SDK streams straight into your alert banner component to warn the user before they book.

Booking details, coordinates, and personal travel data are processed entirely within ephemeral V8 isolates. The server never stores your payment details or passenger names. All transaction payloads transit securely via HTTPS directly to the regional operator API.

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