How to Use the Affinda MCP in Vercel AI SDK

Q: How do I set up the Affinda MCP Server with Vercel AI SDK?

Install @ai-sdk/mcp and call createMCPClient with your Vinkius HTTP endpoint. Pass the tools directly to streamText to let your agent parse documents on the fly. Always remember to call mcpClient.close() when the session ends.

Q: Can I stream live parsing status using Affinda and Vercel AI SDK?

Yes, you can run getdocument inside a streaming text loop to show real-time parsing updates. This keeps your React UI updated with the exact processing status of the invoice or resume.

Q: How does the Vercel AI SDK handle Affinda workspace lists?

The SDK calls the listworkspaces tool to fetch your active document containers. Your LLM agent processes this list and outputs a clean JSON array directly to your frontend components.

Stream parsed invoices and resumes directly into your Next.js frontend with Vercel AI SDK and the Affinda MCP Server.

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Connect Affinda MCP to Vercel AI SDK

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

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Real-time Affinda extraction in AI SDK

The `create_document` tool kicks off synchronous document parsing directly inside your edge-compatible runtime. Your UI gets the structured JSON back instantly, letting you render parsed fields on the screen while the user watches. By using the Vercel AI SDK with this MCP Server, you don't make your users stare at a loading spinner. The application fetches the parsed resume or invoice data and streams it straight into your React state.

Dynamic workspace selection for UI components

The `list_workspaces` tool lets your Vercel AI SDK client fetch all active document containers on the fly. This means your UI can dynamically build dropdown menus for users to choose where their files go. Once selected, the agent uses `list_documents` to show a live feed of processed files. You get a clean, reactive dashboard built on top of your existing Next.js layout without writing custom API routes.

Instant parser matching using AI SDK tools

The `list_document_types` tool tells your Vercel AI SDK application exactly what models your account supports. If a user uploads an ID, the agent identifies the passport parser and routes the file correctly. Your frontend asks the MCP Server for the schema, gets the structure, and uses `get_document` to pull the final JSON. You get clean types and fast UI updates in one go.

Setup guide

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

Install `@ai-sdk/mcp` and call `createMCPClient` with your Vinkius HTTP endpoint. Pass the tools directly to `streamText` to let your agent parse documents on the fly. Always remember to call `mcpClient.close()` when the session ends.

Yes, you can run `get_document` inside a streaming text loop to show real-time parsing updates. This keeps your React UI updated with the exact processing status of the invoice or resume.

The SDK calls the `list_workspaces` tool to fetch your active document containers. Your LLM agent processes this list and outputs a clean JSON array directly to your frontend components.

Yes, the client runs on Vercel Edge Functions without issues. You get fast startup times and low latency when querying document statuses.

All document transmission occurs via Vinkius's zero-trust V8 sandbox using secure HTTPS endpoints. Your raw PDFs, resumes, and invoices are processed directly by the API without lingering in intermediate databases.

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