How to Use the Fairing MCP in Vercel AI SDK

Q: How do I configure the Fairing MCP Server inside a Vercel AI SDK project?

Install @ai-sdk/mcp and create an HTTP client pointing to your Vinkius endpoint. Pass the tools from mcpClient.tools() into streamText or generateText so your agent can call listresponses on demand. Always close the connection with mcpClient.close() once the execution finishes.

Q: Can my agent query specific customer survey histories?

Yes. Your agent can call listcustomers to find a specific buyer and then use getcustomerresponses to fetch their full zero-party data history. This is perfect for building personalized post-purchase UI flows.

Feed real-time post-purchase survey data directly into your React components using Vercel AI SDK and the Fairing MCP Server.

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Connect Fairing MCP to Vercel AI SDK

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

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Render live responses in Vercel AI SDK

Stop making your users wait for heavy analytics dashboards to load. When you hook this MCP Server up to your streaming frontend, your agent pulls raw survey data using `list_responses` and immediately pushes the JSON chunks to the client. Your React components can parse the incoming stream to show live feedback cards. Use `get_response` to pull a deep dive on a specific customer answer the second your agent identifies a trend in the stream.

Inspect active survey questions on the edge

Run your data analysis right on the edge without cold-start penalties. Your agent uses `list_questions` to grab your active post-purchase queries and feeds them into your LLM prompt within your Edge Function. From there, you can use `get_question` to inspect the exact configuration of your high-performing queries. This keeps your serverless execution times low while giving your frontend instant access to your marketing setup.

Stream zero-party insights to your UI

Skip the backend database setup for your internal admin panels. Your agent calls `get_insights` through the Vercel AI SDK and displays aggregated customer sentiment graphs before the page even finishes loading. If a specific metric looks off, the agent can instantly trigger `list_surveys` to check which active campaigns are skewing the numbers. You get real-time observability into customer sentiment without writing complex API polling logic.

Setup guide

Set up Fairing 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 Fairing 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 Fairing 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 Fairing. 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

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

Built-in savings

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Common questions about Fairing MCP in Vercel AI SDK

Install `@ai-sdk/mcp` and create an HTTP client pointing to your Vinkius endpoint. Pass the tools from `mcpClient.tools()` into `streamText` or `generateText` so your agent can call `list_responses` on demand. Always close the connection with `mcpClient.close()` once the execution finishes.

Yes, the server runs in a zero-trust V8 isolate on Vinkius, making it fully compatible with Edge runtimes. Your agent can quickly pull data using `get_insights` without hitting cold-start bottlenecks or bloating your deployment size.

Vinkius manages the authentication layer, so you only need a single endpoint token. Pass this token in your `createMCPClient` transport setup to securely run tools like `get_account_info` without managing multiple API keys in your frontend code.

Yes. Your agent can call `list_customers` to find a specific buyer and then use `get_customer_responses` to fetch their full zero-party data history. This is perfect for building personalized post-purchase UI flows.

All zero-party survey responses and customer feedback data are processed in ephemeral, isolated V8 sandboxes. Vinkius never stores your raw API payloads, meaning your marketing data stays strictly between Fairing and your secure Next.js application.

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