How to Use the Azure Cognitive Search MCP in Vercel AI SDK

Q: How do I stream Azure Cognitive Search results using the Vercel AI SDK?

Call mcpClient.tools() to get tools like searchdocuments and pass them directly to streamText. The results flow straight into your React components in real-time.

Q: Can I handle user-specific Azure Cognitive Search permissions in Vercel AI SDK?

Yes. Use the authProvider option in createMCPClient to supply dynamic Azure credentials based on the active user session.

Q: How does the agent know which Azure index to query?

The agent calls listindexes to inspect available schemas, then selects the matching index before running searchdocuments.

Stream live Azure search queries directly into your React or Next.js UI using the Vercel AI SDK.

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Connect Azure Cognitive Search MCP to Vercel AI SDK

Create your Vinkius account to connect Azure Cognitive Search 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 Azure Cognitive Search with Vercel AI SDK

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Stream vector search results to your Vercel AI SDK app

`vector_search` performs KNN vector queries against Azure embedding profiles to feed raw coordinates directly to your Vercel AI SDK stream. Your Next.js frontend renders these matches instantly as they arrive from the edge. By bypassing heavy backend processing, this MCP Server lets you paint search results on the user's screen before the LLM even finishes its thought. You avoid the dreaded loading spinner entirely.

Fetch index documents without blocking the UI thread

`get_document` pulls a single document using its UUID key to resolve specific data points inside your Edge Functions. The Vercel AI SDK hooks this tool directly into `streamText` so users watch the document content load dynamically. This setup keeps your edge runtimes lightweight. You don't have to bundle heavy SDKs when this MCP Server handles the raw HTTP handshake to Azure on the fly.

Expose Azure Search index status in real-time

`list_indexers` exposes scheduled Azure Search indexers directly to your Vercel AI SDK client during live chat sessions. Your app can monitor data ingestion pipelines and report status changes as they happen. If an indexer stalls, your agent catches it using `list_indexes` and `list_skillsets` to diagnose mapping errors. This puts debugging power directly into your production chat interface.

Setup guide

Set up Azure Cognitive Search 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 Azure Cognitive Search 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 Azure Cognitive Search transactions",
});

console.log(text);
await mcpClient.close();

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Azure Cognitive Search. 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 Azure Cognitive Search MCP in Vercel AI SDK

Call `mcpClient.tools()` to get tools like `search_documents` and pass them directly to `streamText`. The results flow straight into your React components in real-time.

Yes. The server runs in a V8 sandbox, meaning your Vercel AI SDK edge functions stay small and fast because they do not bundle the heavy Azure SDK.

Yes. Use the `authProvider` option in `createMCPClient` to supply dynamic Azure credentials based on the active user session.

The agent calls `list_indexes` to inspect available schemas, then selects the matching index before running `search_documents`.

Your document payloads, UUID keys, and embedding vectors never touch external servers. All traffic routes through an ephemeral, zero-trust V8 sandbox that destroys itself after the request.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

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