Cube.dev MCP Server for Vercel AI SDKGive Vercel AI SDK instant access to 15 tools to Check Live, Check Ready, Convert Query, and more

Name: Cube.dev
Price: 29 USD
Availability: InStock
Rating: 0.2 (1 reviews)
Author: Vinkius

GDPR Free for Subscribers

The Vercel AI SDK is the TypeScript toolkit for building AI-powered applications. Connect Cube.dev through Vinkius and every tool is available as a typed function. ready for React Server Components, API routes, or any Node.js backend.

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The Cube.dev MCP Server for Vercel AI SDK is a standout in the Brain Trust category — giving your AI agent 15 tools to work with, ready to go from day one.

Built for AI Agents by Vinkius

Vinkius delivers Streamable HTTP and SSE to any MCP client

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+ other MCP clients

typescript

import { createMCPClient } from "@ai-sdk/mcp";
import { generateText } from "ai";
import { openai } from "@ai-sdk/openai";

async function main() {
  const mcpClient = await createMCPClient({
    transport: {
      type: "http",
      // Your Vinkius token. get it at cloud.vinkius.com
      url: "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
    },
  });

  try {
    const tools = await mcpClient.tools();
    const { text } = await generateText({
      model: openai("gpt-4o"),
      tools,
      prompt: "Using Cube.dev, list all available capabilities.",
    });
    console.log(text);
  } finally {
    await mcpClient.close();
  }
}

main();

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About Cube.dev MCP Server

Connect your Cube.dev instance to any AI agent to bridge the gap between natural language and your data warehouse. This server allows your agent to interact with Cube's semantic layer, ensuring consistent metrics and high-performance data retrieval.

The Vercel AI SDK gives every Cube.dev tool full TypeScript type inference, IDE autocomplete, and compile-time error checking. Connect 15 tools through Vinkius and stream results progressively to React, Svelte, or Vue components. works on Edge Functions, Cloudflare Workers, and any Node.js runtime.

What you can do

Data Querying — Execute complex REST API queries using load_query to fetch aggregated data with measures, dimensions, and filters.
SQL Inspection — Use get_sql and execute_cube_sql to debug or run raw queries against the SQL API for deep data investigation.
Metadata Exploration — Retrieve cube definitions, views, and segments via get_meta to understand your data model without leaving the chat.
Performance Management — Trigger and monitor background pre-aggregation builds with trigger_pre_aggregation_job to ensure your dashboards stay fast.
Cloud Management — List deployments and environments if using Cube Cloud to manage your infrastructure context.

trigger

Trigger pre aggregation job on Cube.dev

Trigger a pre-aggregation build job

Connect Cube.dev to Vercel AI SDK via MCP

Follow these steps to wire Cube.dev into Vercel AI SDK. The entire setup takes under two minutes — your credentials stay safe behind Vinkius.

Install dependencies

Run npm install @ai-sdk/mcp ai @ai-sdk/openai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the script

Save to agent.ts and run with npx tsx agent.ts

Explore tools

The SDK discovers 15 tools from Cube.dev and passes them to the LLM

Why Use Vercel AI SDK with the Cube.dev MCP Server

Vercel AI SDK provides unique advantages when paired with Cube.dev through the Model Context Protocol.

TypeScript-first: every MCP tool gets full type inference, IDE autocomplete, and compile-time error checking out of the box

Framework-agnostic core works with Next.js, Nuxt, SvelteKit, or any Node.js runtime. same Cube.dev integration everywhere

Built-in streaming UI primitives let you display Cube.dev tool results progressively in React, Svelte, or Vue components

Edge-compatible: the AI SDK runs on Vercel Edge Functions, Cloudflare Workers, and other edge runtimes for minimal latency

Cube.dev + Vercel AI SDK Use Cases

Practical scenarios where Vercel AI SDK combined with the Cube.dev MCP Server delivers measurable value.

AI-powered web apps: build dashboards that query Cube.dev in real-time and stream results to the UI with zero loading states

API backends: create serverless endpoints that orchestrate Cube.dev tools and return structured JSON responses to any frontend

Chatbots with tool use: embed Cube.dev capabilities into conversational interfaces with streaming responses and tool call visibility

Internal tools: build admin panels where team members interact with Cube.dev through natural language queries

Example Prompts for Cube.dev in Vercel AI SDK

Ready-to-use prompts you can give your Vercel AI SDK agent to start working with Cube.dev immediately.

"Show me the metadata for all available cubes and views."

"Run a query to get the total count of orders grouped by status for the last 30 days."

"Trigger a pre-aggregation build for the 'Sales' cube."

Troubleshooting Cube.dev MCP Server with Vercel AI SDK

Common issues when connecting Cube.dev to Vercel AI SDK through Vinkius, and how to resolve them.

createMCPClient is not a function

Install: npm install @ai-sdk/mcp

Cube.dev + Vercel AI SDK FAQ

Common questions about integrating Cube.dev MCP Server with Vercel AI SDK.

How does the Vercel AI SDK connect to MCP servers?

Import createMCPClient from @ai-sdk/mcp and pass the server URL. The SDK discovers all tools and provides typed TypeScript interfaces for each one.

Can I use MCP tools in Edge Functions?

Yes. The AI SDK is fully edge-compatible. MCP connections work on Vercel Edge Functions, Cloudflare Workers, and similar runtimes.

Does it support streaming tool results?

Yes. The SDK provides streaming primitives like useChat and streamText that handle tool calls and display results progressively in the UI.

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