How to Use the Medallia MCP in Vercel AI SDK

Connect Medallia to Vercel AI SDK to stream real-time customer feedback directly into your React or Next.js user interfaces.

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Connect Medallia MCP to Vercel AI SDK

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

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Real-time survey data streaming

Pipe live customer feedback directly into your frontend components. Use `list_surveys` and `list_responses` to feed your UI without waiting for background batch processes. Your users see data materialize as the AI client fetches it. It removes the friction of loading states by pushing live metrics straight to the browser.

Targeted alert monitoring

Surface critical customer issues immediately by calling `get_alert` within your streaming logic. This MCP server pushes specific feedback events to your dashboard the moment they hit the system. You avoid polling overhead by reacting only when the AI client identifies a high-priority response. Keep your interface focused on the data that demands immediate attention.

Programmatic experience tracking

Query your entire feedback infrastructure using `list_programs` and `get_program_details`. You gain a live view of which surveys are active across your global business units. This gives your application the context it needs to render relevant feedback widgets. Stop hardcoding survey IDs and let your agent pull the current configuration dynamically.

Setup guide

Set up Medallia 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 Medallia 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 Medallia transactions",
});

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

Get your connection token →

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Why Choose Vinkius

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

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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 Medallia MCP in Vercel AI SDK

Install the MCP client package and initialize it with your server endpoint. You then pass the tools directly into your streamText function to start querying data.

Yes, it manages the connection via streaming. You can paginate through results using the tool parameters to keep your memory usage predictable.

The connection uses an ephemeral tunnel. Data only touches the memory of your active session and never persists on the transport layer.

The server returns structured JSON which the SDK parses into your UI. You map these objects to your existing React components exactly as you would with any local API.

The client detects the disconnect immediately. You can implement a standard retry block to re-establish the transport without losing your current state.

Use it with your favorite AI tools

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