How to Use the Emma MCP in Vercel AI SDK

Q: Can I list Emma members using Vercel AI SDK?

Absolutely. Just call listmembers within your agent flow. The results are returned as a JSON object you can map directly to your table components.

Get real-time email data inside your Vercel AI SDK interface without waiting for loading spinners.

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…and any MCP-compatible client

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Connect Emma MCP to Vercel AI SDK

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

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Stream mailing stats into your UI

Feed live mailing performance metrics directly into your React or Next.js components. When your AI agent calls `get_mailing_stats`, the numbers render instantly for the end user. Stop forcing users to wait for backend polling. This MCP Server pushes results through your streaming pipeline so the interface stays responsive while data arrives.

Manage members with AI-SDK

Your agent can fetch specific subscriber details using `get_member` or browse entire lists with `list_members`. Everything happens in the same execution context as your other UI logic. This keeps your frontend code clean. You don't need separate API routes for basic Emma operations when the agent handles lookups on the fly.

Automate group organization

Create and manage segmentation logic using `create_group` and `list_groups` directly from your chat surface. It turns static list management into a conversational interaction. Just be careful with `delete_group`. Since this runs in your production environment, ensure your UI requires a confirmation step before the agent executes destructive changes.

Setup guide

Set up Emma 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 Emma 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 Emma 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 Emma. 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.

Why Choose Vinkius

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

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place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about Emma MCP in Vercel AI SDK

You connect the server via your transport configuration and pass the tools into `streamText`. The output flows naturally into your UI components.

Yes, the tools are compatible with the SDK's streaming architecture. You get the data in your frontend as soon as the agent finishes the call.

Absolutely. Just call `list_members` within your agent flow. The results are returned as a JSON object you can map directly to your table components.

Your app will receive an error response from the tool. You should handle these cases in your client-side error boundaries to keep the UI stable.

Your credentials never hit the browser. The Vercel AI SDK runs the tool logic on your server, keeping your private member PII away from the client-side bundle.

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