How to Use the Alation MCP in Vercel AI SDK

Q: How do I connect Alation to Vercel AI SDK?

Install @ai-sdk/mcp and initialize your client with createMCPClient. Point the HTTP transport URL to your Vinkius endpoint to start loading tools.

Q: Can Vercel AI SDK read custom governance fields from Alation?

Yes. Pass the listcustomfields tool into your generateText or streamText calls. The model will read your organization's specific compliance tags and data stewardship notes.

Q: Does the Vercel AI SDK integration support OAuth for Alation?

It does. You can configure the authProvider in your MCP client setup to handle user-level authentication. This guarantees the agent only sees catalogs the current user has permission to view.

Connect Alation to your Next.js frontend with Vercel AI SDK to stream live data catalog metadata straight to your users.

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Connect Alation MCP to Vercel AI SDK

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

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Stream Alation asset discovery via Vercel AI SDK

Your users don't want to stare at a loading spinner while your app searches through enterprise data dictionaries. By wiring up the `search_catalog` tool, your React frontend renders matching data sources and tables as the language model finds them. The text appears on screen instantly. Drilling down into specific schemas happens just as fast. When a user asks what lives inside a specific database, the agent calls `list_schemas` and `list_tables` to pull the exact structure. You get a live, interactive data catalog explorer built right into your custom UI.

Surface data lineage instantly

Tracing where a dashboard metric came from usually means digging through three different Alation screens. Now your agent can execute `get_lineage` behind the scenes and stream the exact upstream dependencies back to the chat window. Adding context is trivial. Once the lineage graph loads, your app can fire off `get_object_metadata` to grab owners, tags, and descriptions. The end user sees a complete picture of the data pipeline without ever leaving your application.

Fetch cached queries directly

Sometimes you just need the actual data, not just the column names. You can pass the `get_query_results` tool to your MCP Server integration, letting the AI pull pre-computed SQL outputs directly from Alation. This keeps your Edge Functions fast. Instead of forcing the LLM to write and execute a new query against a live warehouse, it grabs the cached results. Your application stays snappy while delivering verified enterprise data.

Setup guide

Set up Alation 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 Alation 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 Alation 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 Alation. 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 Alation MCP in Vercel AI SDK

Install `@ai-sdk/mcp` and initialize your client with `createMCPClient`. Point the HTTP transport URL to your Vinkius endpoint to start loading tools.

Yes. Pass the `list_custom_fields` tool into your `generateText` or `streamText` calls. The model will read your organization's specific compliance tags and data stewardship notes.

You skip the boilerplate. The Vinkius endpoint gives your AI client immediate access to ten formatted tools like `list_columns` and `list_data_sources` without writing custom fetch logic or managing complex authentication headers.

It does. You can configure the `authProvider` in your MCP client setup to handle user-level authentication. This guarantees the agent only sees catalogs the current user has permission to view.

Vinkius runs your connection inside an ephemeral V8 Isolate sandbox. When your app fetches schema names, table columns, or cached query results, the data passes through a zero-trust tunnel. We never store your data dictionaries.

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