How to Use the AlisQI MCP in Vercel AI SDK

Q: How do I connect AlisQI to my Vercel AI SDK project?

You'll use the createMCPClient function from @ai-sdk/mcp. Just pass your Vinkius endpoint URL in the transport options. Then you can provide the AlisQI tools to generateText or streamText.

Q: Can I filter AlisQI quality results using the Vercel AI SDK?

Yes. The listresults tool accepts filter parameters. Your agent can construct a query to find AlisQI results based on status, date, or other fields, giving you precise control over the data streamed to your UI.

Build UIs that stream AlisQI quality data in real time with the Vercel AI SDK.

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Connect AlisQI MCP to Vercel AI SDK

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

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Live Quality Dashboards

This MCP Server gives your Vercel AI SDK project the tools to query AlisQI and build live dashboards. Your React or Next.js components won't wait for a full data load; results stream directly into the UI, appearing as they arrive. Your agent can call `list_analysis_sets` to populate a dropdown, and then use `list_results` to fill a table with data from the selected set. Because you're using the AI SDK, that table populates row-by-row, right in front of the user. It feels fast because it is.

Drill Down into Details

The server includes tools like `get_result_details` so your app can investigate specific quality events without a page refresh. When a user clicks a result in your UI, your agent can instantly call the tool to fetch the specifics for that one record. If there are documents attached, you're covered. The `get_result_attachments` tool provides a list of associated files. You can then build links for users to download inspection photos or compliance documents directly from your interface.

Update QMS Data via Chat

Use the `store_results` tool to build an interface where users can update the QMS just by talking to your AI. Your agent can interpret a user's request, construct the right payload, and use the tool to create or update a record in AlisQI. This isn't just a simple form submission. The AI can handle partial information, ask clarifying questions, and then confirm the action. You're building a conversational front-end for your quality management system, powered by this AlisQI MCP Server.

Setup guide

Set up AlisQI 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 AlisQI 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 AlisQI 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 AlisQI. 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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Common questions about AlisQI MCP in Vercel AI SDK

You'll use the `createMCPClient` function from `@ai-sdk/mcp`. Just pass your Vinkius endpoint URL in the transport options. Then you can provide the AlisQI tools to `generateText` or `streamText`.

Yes. The `list_results` tool accepts filter parameters. Your agent can construct a query to find AlisQI results based on status, date, or other fields, giving you precise control over the data streamed to your UI.

You can build anything from live monitoring dashboards and data exploration tools to conversational interfaces for updating quality records. Since the Vercel AI SDK streams data, it's perfect for creating responsive, real-time user experiences on top of your AlisQI data.

It's straightforward. After subscribing on Vinkius, you get a single endpoint token. In your code, you install the `@ai-sdk/mcp` package and point the client to your URL. That's it.

Your AlisQI quality results and attachments are processed in an ephemeral Vinkius sandbox for each request. Vinkius handles the auth token securely, so your app and the Vercel Edge Functions never have to store credentials.

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