How to Use the Userback MCP in Vercel AI SDK

Q: How do I get a list of Userback projects using the Vercel AI SDK?

You call listuserbackprojects through the MCP Client. The tool returns an array of project identifiers that you can then display in your UI immediately.

Q: What happens if I need to create a new feedback entry with Vercel AI SDK?

You use createfeedbackentry by providing the necessary bug details. The agent sends this data, and you can confirm success or failure directly in your streaming UI.

Q: Does the MCP Server support listing all Userback feedbacks with Vercel AI SDK?

Yes, listfeedbacks retrieves all available feedback records. You get these results streamed right into your React or Next.js components for real-time display.

Q: When calling the MCP Server, what data type is handled by Userback?

This MCP Server primarily deals with structured feedback entries. These are the detailed reports that include annotated screenshots and bug descriptions.

Q: Can I get user details using Userback and Vercel AI SDK?

You can run listaccountusers to grab all available account users. The results stream back, letting you populate a user roster on your frontend.

Stream live user feedback data directly into your Next.js or React frontend using Vercel AI SDK.

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Connect Userback MCP to Vercel AI SDK

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

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Displaying Feedback in Real Time

The `list_feedbacks` tool lets you fetch all Userback submissions and stream them directly to the client UI. Because your agent handles the streaming, users see new feedback appear immediately—no loading spinner required. You can also use `get_feedback_details` to pull a specific report's data and show it live on screen. This makes the entire user experience feel snappier and more responsive.

Managing Project Data via MCP Server

Need project context for your feedback? The `get_project_details` tool pulls all the necessary data points you need to display next to a bug report. This keeps your frontend code clean because it handles fetching related information. Use `list_userback_projects` first. You get a list of available projects, and then you pass one ID into this MCP Server for full details.

Listing User Accounts in the UI

The `list_account_users` tool gives you an array of all users associated with your account. You can stream this list to a dashboard and show active user counts instantly. If you need to know more about one person, you'll use that ID later with other tools. This makes tracking down who submitted what feedback simple for your frontend.

Setup guide

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

You call `list_userback_projects` through the MCP Client. The tool returns an array of project identifiers that you can then display in your UI immediately.

You use `create_feedback_entry` by providing the necessary bug details. The agent sends this data, and you can confirm success or failure directly in your streaming UI.

Yes, `list_feedbacks` retrieves all available feedback records. You get these results streamed right into your React or Next.js components for real-time display.

This MCP Server primarily deals with structured `feedback entries`. These are the detailed reports that include annotated screenshots and bug descriptions.

You can run `list_account_users` to grab all available account users. The results stream back, letting you populate a user roster on your frontend.

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