How to Use the Navitia MCP in Vercel AI SDK

Q: Can I stream live transit disruption alerts to my frontend?

Yes, you can. By calling getdisruptions through the Vercel AI SDK, the agent streams active alerts directly into your UI components, updating the user interface as soon as the model identifies a transit delay.

Q: How does the Navitia MCP Server resolve ambiguous stop names in Vercel AI SDK?

The agent uses searchplaces to match user input against transit stops and addresses. It returns a list of candidate locations, allowing your Vercel AI SDK interface to render an autocomplete list for the user to select the correct station.

Q: Does this setup support rendering isochrone maps?

It does. The agent invokes getisochrone to generate GeoJSON polygon data, which your Vercel AI SDK application can pass directly to Mapbox or Leaflet components to render reachable areas on a map.

Stream public transit routes and live schedules directly into your Next.js frontend with Vercel AI SDK and Navitia.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect Navitia MCP to Vercel AI SDK

Create your Vinkius account to connect Navitia 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.

GDPR Free for Subscribers

Setup Navitia with Vercel AI SDK

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Stream live transit boards using Vercel AI SDK

The `get_departures` and `get_arrivals` tools let your agent stream real-time transit boards directly into React components. Your Next.js users don't have to stare at static loading spinners while waiting for schedules. You can trigger UI changes instantly based on incoming transit parameters. If a user asks for alternative routes, the model invokes `get_stop_schedule` to populate a live timetable.

Map European transit coverage on the edge

The `get_coverage` tool verifies whether a user's city is supported before triggering heavy route computations. Deploying to Vercel's edge network means your transit agent needs to run fast without hitting dead ends. Finding nearby stations becomes a zero-cold-start operation. The agent uses `get_nearby_stops` to pull coordinates and immediately feeds them into your map components.

Fast multimodal route planning in React

The `plan_journey` tool calculates multi-modal paths including trains, buses, and bikes directly within your Next.js application. Building a responsive trip planner requires handling these complex transit queries without blocking the main thread. Handling disruptions during a live chat requires immediate feedback. The agent queries `get_disruptions` to warn users about active delays on their route.

Setup guide

Set up Navitia 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 Navitia 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 Navitia transactions",
});

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

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 Navitia. 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.

Why Choose Vinkius

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

Connect Navitia now

Real-time monitoring

Live

visibility into every interaction

Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

60%

lower AI costs

Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about Navitia MCP in Vercel AI SDK

You should implement caching at the edge or use Vercel's KV store to cache responses from tools like `get_stop_schedule` and `get_lines`. This prevents your agent from hitting Navitia's limits during high-traffic periods while keeping your AI responses fast.

Yes, you can. By calling `get_disruptions` through the Vercel AI SDK, the agent streams active alerts directly into your UI components, updating the user interface as soon as the model identifies a transit delay.

The agent uses `search_places` to match user input against transit stops and addresses. It returns a list of candidate locations, allowing your Vercel AI SDK interface to render an autocomplete list for the user to select the correct station.

It does. The agent invokes `get_isochrone` to generate GeoJSON polygon data, which your Vercel AI SDK application can pass directly to Mapbox or Leaflet components to render reachable areas on a map.

Every coordinate, search query, and transit route request processed by this MCP server runs within Vinkius's isolated V8 sandbox. This means your users' location coordinates and travel itineraries are never stored or exposed to external networks, maintaining strict transit data privacy.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

OpenAI Agents SDK sdk-python

Google ADK sdk-python

Pydantic AI sdk-python

Vercel AI SDK sdk-typescript