How to Use the Document360 MCP in Vercel AI SDK

Q: How do I connect the Document360 MCP Server to my Vercel AI SDK project?

Install the @ai-sdk/mcp package and create an HTTP transport client pointing to your Vinkius endpoint. Pass the tools from mcpClient.tools() directly into the tools parameter of streamText, then close the connection when the request finishes.

Q: Does Vercel AI SDK support searching multiple Document360 project versions?

It does. Your agent first calls listprojects to identify the correct version ID, then uses that ID to filter subsequent searches or category listings.

Q: How does the analytics tool work with streaming interfaces?

The agent calls analytics to grab view counts or search trends, then streams a formatted summary directly to your admin dashboard. This lets you build live documentation health monitors without writing complex backend charts.

Feed live Document360 knowledge base articles directly into your React frontends using the Vercel AI SDK.

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Connect Document360 MCP to Vercel AI SDK

Create your Vinkius account to connect Document360 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 Document360 with Vercel AI SDK

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Render live Document360 searches with Vercel AI SDK

Look, nobody wants to stare at a loading spinner when using the `search` tool. When you pair the Vercel AI SDK with this MCP Server, your app streams live search results directly into your custom React components. Your agent triggers `list_categories` behind the scenes to map out the structure. It displays matching records instantly, keeping the UI responsive while the LLM formats the documentation links on the fly.

Fetch raw article content straight to edge functions

Stop making your users wait for massive page reloads when the `get_article` tool can fetch specific technical details instantly. You run the query directly inside your edge-compatible routes to pull raw documentation nodes. The Vercel AI SDK grabs the raw markdown or HTML payload directly. Your agent processes the raw text and outputs a concise summary straight to the user's chat window.

Build a dynamic portal with live category drill-downs

Build a documentation browser that updates as your writers publish by querying `list_projects` to find the active version. The agent then calls `list_articles` to map out the entire active workspace. No static rebuilding required for your Next.js site. The SDK handles the stream, rendering the updated category tree in real time as the underlying Document360 workspace changes.

Setup guide

Set up Document360 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 Document360 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 Document360 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 Document360. 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 Document360 MCP in Vercel AI SDK

Install the `@ai-sdk/mcp` package and create an HTTP transport client pointing to your Vinkius endpoint. Pass the tools from `mcpClient.tools()` directly into the `tools` parameter of `streamText`, then close the connection when the request finishes.

Yes, you can. The SDK allows you to map the JSON payload from the `search` tool directly to UI components, showing users matched articles as they are found.

It does. Your agent first calls `list_projects` to identify the correct version ID, then uses that ID to filter subsequent searches or category listings.

The agent calls `analytics` to grab view counts or search trends, then streams a formatted summary directly to your admin dashboard. This lets you build live documentation health monitors without writing complex backend charts.

Vinkius runs the MCP Server in an isolated sandbox and handles your API credentials securely. The server only accesses your articles, categories, and team lists when your Vercel AI SDK agent explicitly invokes a tool, keeping your proprietary documentation private.

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