How to Use the vCard Contacts Parser MCP in Vercel AI SDK

Q: Where can I find the documentation for vCard Contacts Parser in Vercel AI SDK?

The tool definitions are exposed via mcpClient.tools(). You'll pass this array of tools directly into your streaming text generation functions.

Real-time data parsing and structured output with Vercel AI SDK.

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Connect vCard Contacts Parser MCP to Vercel AI SDK

Create your Vinkius account to connect vCard Contacts Parser 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 vCard Contacts Parser with Vercel AI SDK

Ask AI about this MCP

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Claude

Perplexity

Stream Structured Data with Vercel AI SDK

Use the `parse_kindle_clippings` tool to take raw text from a Kindle's 'My Clippings.txt' file. It spits out structured JSON, making highlights, notes, and bookmarks easy to use. When you run this through your AI client, the resulting data streams directly into the UI. The user sees the parsed contact records or clippings appear live, skipping that slow loading spinner.

Process vCard Contacts Parser Outputs

The MCP Server can handle converting messy exports—like iPhone and Android `.vcf` files—into clean JSON. This makes the AI client a genuinely smart local address book. You call `mcpClient.tools()` to expose this tool, letting your front-end components react immediately when structured data arrives.

Handle Complex Data Extraction

You don't just get text back; you get actionable structures. The parser groups clippings by the book they came from and isolates specific elements like notes or bookmarks. This means your agent can instantly read a large amount of source material and present it in clean, consumable fields.

Setup guide

Set up vCard Contacts Parser 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 vCard Contacts Parser 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 vCard Contacts Parser 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 vcard-parser. 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 vCard Contacts Parser MCP in Vercel AI SDK

Your agent sends the raw contact export (like a .vcf file) to the server. The MCP Server processes it and returns clean JSON data, which your Vercel AI SDK client then streams right into your Next.js or Svelte UI.

Absolutely. Since the tool result streams directly to the UI via the Vercel AI SDK, it works perfectly within an Edge Function environment for real-time updates.

Yes. You can pass the raw 'My Clippings.txt' content to the `parse_kindle_clippings` tool. The result is structured JSON, making those highlights immediately usable in your client code.

This server primarily handles contact records and other textual exports like Kindle clippings. It converts these into reliable JSON structures for your agent to consume.

The tool definitions are exposed via `mcpClient.tools()`. You'll pass this array of tools directly into your streaming text generation functions.

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