How to Use the Uber MCP in Vercel AI SDK

Q: How does Uber MCP Server help with ride planning when using Vercel AI SDK?

You can let your agent run getplaceautocomplete first to validate the user's intended pickup spot. Then, use that validated location in getpriceestimate to give them an immediate cost comparison before they even book.

Q: What data does Uber MCP Server handle when using Vercel AI SDK?

The server touches user profile data via getuserprofile, which confirms the authenticated account. It also handles location coordinates and trip history details, like dates, distances, and prices.

Q: Can Uber MCP Server speed up booking flow with Vercel AI SDK?

Absolutely. Use gettimeestimate to show users how quickly an Uber can arrive at a location. This real-time data helps them decide if they need the service right away.

Q: What should I do with trip history when using Vercel AI SDK?

You use gettriphistory to pull up past rides. Your agent can then summarize expenses or show a map view of where they've been, which is great for billing summaries.

Real-time ride management data streaming directly into your Vercel AI SDK frontends.

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Connect Uber MCP to Vercel AI SDK

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

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View saved locations with the Uber MCP Server

Don't make users type addresses. Use `get_saved_places` to instantly list all stored spots, letting them select a pickup or dropoff point right in your UI. This tool returns aliases, full addresses, and coordinates for every saved location. It’s perfect for building quick trip request forms where speed matters.

Estimate prices using the Uber MCP Server

Need to show users how much a ride will cost? You can grab a general idea with `get_price_estimate` by inputting two locations. It compares costs across different types of rides in local currency. For more precision, use `get_ride_estimate`. This targets one specific product and gives you the exact price before the user clicks 'Book'. The results stream right to your UI.

Autocomplete locations with the Uber MCP Server

Building a ride-hailing app means users need fast location input. `get_place_autocomplete` helps solve this by taking the user's current spot as bias. It returns structured address components and place descriptions. This lets your AI client suggest valid pickup or dropoff locations in real time, making the whole booking process feel instant.

Setup guide

Set up Uber 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 Uber 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 Uber 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 Uber. 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 Uber MCP in Vercel AI SDK

You can let your agent run `get_place_autocomplete` first to validate the user's intended pickup spot. Then, use that validated location in `get_price_estimate` to give them an immediate cost comparison before they even book.

The server touches user profile data via `get_user_profile`, which confirms the authenticated account. It also handles location coordinates and trip history details, like dates, distances, and prices.

Absolutely. Use `get_time_estimate` to show users how quickly an Uber can arrive at a location. This real-time data helps them decide if they need the service right away.

You use `get_trip_history` to pull up past rides. Your agent can then summarize expenses or show a map view of where they've been, which is great for billing summaries.

The server touches user location coordinates (latitude/longitude) and trip history records. These are critical pieces of movement data that require careful handling in your application logic.

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