How to Use the WhatsApp Chat Export Parser MCP in Vercel AI SDK

Q: How do I search for specific names using WhatsApp Chat Export Parser and the Vercel AI SDK?

Just call parsewhatsappchat with your file. Your agent client will handle the extraction of senders and timestamps, letting you filter chat transcripts by name or date range in real-time.

Q: What if I need to summarize long threads using WhatsApp Chat Export Parser and Vercel AI SDK?

After parsewhatsappchat cleans the chat transcripts into JSON, your agent can feed that clean data directly into a summarization model. It's fast because the data is already structured.

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Connect WhatsApp Chat Export Parser MCP to Vercel AI SDK

Create your Vinkius account to connect WhatsApp Chat Export 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 WhatsApp Chat Export Parser with Vercel AI SDK

Ask AI about this MCP

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Claude

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Live Chat Data Streaming

The `parse_whatsapp_chat` tool takes messy exported WhatsApp files and immediately structures them into JSON. When you call this MCP Server via your Vercel AI SDK, the results stream directly to your frontend. You won't wait for a spinner anymore. Users see the data appearing live as your agent works, making the whole experience feel instant.

Analyzing Text Transcripts

Need to dig through years of chat history? The `parse_whatsapp_chat` tool handles that by extracting key elements like senders, timestamps, and message content. This MCP Server lets your agent search deep within the chat transcripts. This is perfect for building user-facing tools where quick analysis of long text files is critical.

Participant Statistics

The tool doesn't just pull messages; it also calculates participant statistics from the exported WhatsApp file. You get a clear count of who messaged and how often. This means your Vercel AI SDK can present more than just text—it gives users actionable metrics right in their UI.

Setup guide

Set up WhatsApp Chat Export 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 WhatsApp Chat Export 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 WhatsApp Chat Export Parser transactions",
});

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

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Common questions about WhatsApp Chat Export Parser MCP in Vercel AI SDK

Just call `parse_whatsapp_chat` with your file. Your agent client will handle the extraction of senders and timestamps, letting you filter chat transcripts by name or date range in real-time.

Yes. Your agent can process multiple chat exports sequentially. You just pass the file path, and the MCP Server handles the parsing for each one, giving you a collection of structured data.

After `parse_whatsapp_chat` cleans the chat transcripts into JSON, your agent can feed that clean data directly into a summarization model. It's fast because the data is already structured.

Absolutely. The MCP Server is designed to work in environments like Edge Functions, meaning you can analyze those chat transcripts without needing a heavy backend server.

This server processes raw text data from chat transcripts. It extracts message content, sender identities, and time stamps for analysis.

Use it with your favorite AI tools

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

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