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Databox MCP Server for Vercel AI SDKGive Vercel AI SDK instant access to 12 tools to Create Data Source, Create Dataset, Delete Dataset, and more

Built by Vinkius GDPR 12 Tools SDK

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

Use with Your AI Agent

Ask AI about this App Connector for Vercel AI SDK

Open in ChatGPT Open in Claude Open in Perplexity

The Databox app connector for Vercel AI SDK is a standout in the Data Analytics category — giving your AI agent 12 tools to work with, ready to go from day one.

Vinkius delivers Streamable HTTP and SSE to any MCP client

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 Databox, list all available capabilities.",
    });
    console.log(text);
  } finally {
    await mcpClient.close();
  }
}

main();
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* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About Databox MCP Server

Connect your Databox account to any AI agent and take full control of your business intelligence and data ingestion workflows through natural conversation.

The Vercel AI SDK gives every Databox tool full TypeScript type inference, IDE autocomplete, and compile-time error checking. Connect 12 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

  • Dataset Orchestration — List and manage your database collections (tables) programmatically, including retrieving detailed schema metadata and primary key configurations
  • High-Fidelity Ingestion — Programmatically push arrays of raw data records directly into Databox to coordinate real-time metric visualization and reporting
  • Source Architecture — Access and manage your directory of data source integrations and connected accounts to maintain high-fidelity data feeds
  • Usage Monitoring — Programmatically track your data storage statistics and API activity logs to coordinate your analytics budget and quotas
  • Operational Visibility — Check authenticated user profiles and verify system connectivity directly through your agent for instant BI reporting

The Databox MCP Server exposes 12 tools through the Vinkius. Connect it to Vercel AI SDK in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

All 12 Databox tools available for Vercel AI SDK

When Vercel AI SDK connects to Databox through Vinkius, your AI agent gets direct access to every tool listed below — spanning kpi-tracking, data-visualization, real-time-dashboards, and more. Every call is secured with network, filesystem, subprocess, and code evaluation entitlements inside a sandboxed runtime. Beyond a simple connection, you get a full AI Gateway with real-time visibility into agent activity, enterprise governance, and optimized token usage.

create_data_source

Create a new data source

create_dataset

Create a new dataset

delete_dataset

Delete a dataset

get_current_user

Get authenticated user profile

get_dataset_details

Get details for a specific dataset

get_storage_statistics

Get data storage stats

list_accounts

List all Databox accounts

list_activity_logs

List API activity logs

list_data_sources

List data sources for an account

list_dataset_metrics

List metrics in a dataset

list_datasets

List all datasets

push_metrics_data

Ingest data into a dataset

Connect Databox to Vercel AI SDK via MCP

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

01

Install dependencies

Run npm install @ai-sdk/mcp ai @ai-sdk/openai
02

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token
03

Run the script

Save to agent.ts and run with npx tsx agent.ts
04

Explore tools

The SDK discovers 12 tools from Databox and passes them to the LLM

Why Use Vercel AI SDK with the Databox MCP Server

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

01

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

02

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

03

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

04

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

Databox + Vercel AI SDK Use Cases

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

01

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

02

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

03

Chatbots with tool use: embed Databox capabilities into conversational interfaces with streaming responses and tool call visibility

04

Internal tools: build admin panels where team members interact with Databox through natural language queries

Example Prompts for Databox in Vercel AI SDK

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

01

"List all datasets in my Databox account."

02

"Push record to 'ds_123': value 1500, date '2026-04-16'."

03

"Show my storage usage and API activity logs."

Troubleshooting Databox MCP Server with Vercel AI SDK

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

01

createMCPClient is not a function

Install: npm install @ai-sdk/mcp

Databox + Vercel AI SDK FAQ

Common questions about integrating Databox MCP Server with Vercel AI SDK.

01

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.
02

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.
03

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.