Google BigQuery MCP Server for Vercel AI SDK 7 tools — connect in under 2 minutes
The Vercel AI SDK is the TypeScript toolkit for building AI-powered applications. Connect Google BigQuery 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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Vinkius supports streamable HTTP and SSE.
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 Google BigQuery, list all available capabilities.",
});
console.log(text);
} finally {
await mcpClient.close();
}
}
main();
* 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 Google BigQuery MCP Server
Connect your Google BigQuery data warehouse to any AI agent and empower it to act as a fractional data analyst. Traverse structured schemas, audit data pipelines, and execute complex aggregations over petabytes of data purely through conversational prompts.
The Vercel AI SDK gives every Google BigQuery tool full TypeScript type inference, IDE autocomplete, and compile-time error checking. Connect 7 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
- Execute Queries — Prompt natively structural Data Analytics requests and allow the LLM to write, run, and summarize exact
Standard SQLinstantly - Discover Schemas — Inspect deep table column mappings, discovering strict clustering logic and native partitioning limits
- Audit Workloads — Paginate recent cluster jobs, identify heavily delayed computations globally, and read bytes explicitly processed by runs
- Dataset Topologies — Traverse nested datasets logically mapping GCP access properties recursively
- Performance Troubleshooting — Read exact job error traces directly confirming syntax failures natively
The Google BigQuery MCP Server exposes 7 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.
How to Connect Google BigQuery to Vercel AI SDK via MCP
Follow these steps to integrate the Google BigQuery MCP Server with Vercel AI SDK.
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 7 tools from Google BigQuery and passes them to the LLM
Why Use Vercel AI SDK with the Google BigQuery MCP Server
Vercel AI SDK provides unique advantages when paired with Google BigQuery 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 Google BigQuery integration everywhere
Built-in streaming UI primitives let you display Google BigQuery 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
Google BigQuery + Vercel AI SDK Use Cases
Practical scenarios where Vercel AI SDK combined with the Google BigQuery MCP Server delivers measurable value.
AI-powered web apps: build dashboards that query Google BigQuery in real-time and stream results to the UI with zero loading states
API backends: create serverless endpoints that orchestrate Google BigQuery tools and return structured JSON responses to any frontend
Chatbots with tool use: embed Google BigQuery capabilities into conversational interfaces with streaming responses and tool call visibility
Internal tools: build admin panels where team members interact with Google BigQuery through natural language queries
Google BigQuery MCP Tools for Vercel AI SDK (7)
These 7 tools become available when you connect Google BigQuery to Vercel AI SDK via MCP:
execute_query
Run an explicit BigQuery Standard SQL command
get_dataset
Get exact details of a specific BigQuery dataset
get_job
Get complete details of a specific BigQuery Job run
get_table
Get explicit metadata and schema details of a pure BigQuery Table
list_datasets
List all explicit Datasets in the active GCP project
list_jobs
List recent explicit BigQuery runtime Jobs securely
list_tables
List explicit Tables natively contained within a Dataset
Example Prompts for Google BigQuery in Vercel AI SDK
Ready-to-use prompts you can give your Vercel AI SDK agent to start working with Google BigQuery immediately.
"Get the table schema for `users_prod` in the `analytics` dataset."
"Find out the top 3 countries with the most signups this month in the `users` table."
"Did the overnight cron job compute successfully or did it fail?"
Troubleshooting Google BigQuery MCP Server with Vercel AI SDK
Common issues when connecting Google BigQuery to Vercel AI SDK through the Vinkius, and how to resolve them.
createMCPClient is not a function
npm install @ai-sdk/mcpGoogle BigQuery + Vercel AI SDK FAQ
Common questions about integrating Google BigQuery MCP Server with Vercel AI SDK.
How does the Vercel AI SDK connect to MCP servers?
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?
Does it support streaming tool results?
useChat and streamText that handle tool calls and display results progressively in the UI.Connect Google BigQuery with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect Google BigQuery to Vercel AI SDK
Get your token, paste the configuration, and start using 7 tools in under 2 minutes. No API key management needed.