How to Use the Looker (Business Intelligence & Data) MCP in Vercel AI SDK

Stream real-time BI metrics from Looker (Business Intelligence & Data) directly into your Vercel AI SDK frontend.

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Connect Looker (Business Intelligence & Data) MCP to Vercel AI SDK

Create your Vinkius account to connect Looker (Business Intelligence & Data) 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 Looker (Business Intelligence & Data) with Vercel AI SDK

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Claude

Perplexity

Dynamic data streaming in your UI

Feed live BI data into your application state using `run_inline_query`. By integrating this MCP server, your frontend receives raw JSON results as the AI processes them, removing the need for intermediary data storage. Your users see the output populate instantly. This bypasses typical loading states and keeps the interaction loop tight for high-frequency data requests.

Dashboard metadata injection

Expose your organizational structure by listing assets with `list_dashboards` and `list_folders`. You get a complete map of your BI environment available to the AI client at runtime. Use `get_dashboard` to pull specific configurations for your UI components. It turns your dashboard IDs into actionable content objects that your interface can render on demand.

Content discovery and audit

Query your entire instance metadata using `search_content` to find relevant reports without manual navigation. This tool maps your existing assets directly to your agent's context window. Verify your data lineage by calling `list_looks` or `get_look` to ensure the AI uses the correct definitions. It keeps your reporting logic synchronized with the source of truth.

Setup guide

Set up Looker (Business Intelligence & Data) 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 Looker (Business Intelligence & Data) 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 Looker (Business Intelligence & Data) 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 Looker. 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 Looker (Business Intelligence & Data) MCP in Vercel AI SDK

You initialize the client via the MCP transport and pass the server tools directly into your `generateText` or `streamText` calls. It maps your BI data functions as native JavaScript tools within the SDK.

Yes. The server handles the authentication handshake, and you control the specific tool access through the client configuration. It ensures your BI environment remains isolated while providing the necessary data to your agent.

It does. Because the MCP server streams results via the transport layer, your UI receives the data packets as they are fetched. This creates a responsive experience for complex dashboard queries.

The server returns a standard error object detailing the API failure. You can catch these in your SDK logic to provide immediate feedback to your users.

The server operates within an ephemeral V8 sandbox. It only touches the specific Looker dashboard and query metadata you explicitly request, keeping your sensitive PII out of the model training loop.

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