How to Use the Gmelius MCP in Vercel AI SDK

Connect Vercel AI SDK to your Gmelius shared inbox to stream live team email data directly into your React or Next.js interface.

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Connect Gmelius MCP to Vercel AI SDK

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

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Real-time inbox monitoring in Vercel AI SDK

Stop guessing if your team is on top of customer requests. Your React frontend pulls live data from shared boards using `list_gmelius_boards` and `list_gmelius_board_cards` to render active tasks without any page refreshes. Your users see conversation updates as they happen. By calling `get_gmelius_conversation`, you push specific email details directly into the chat stream for immediate context.

Automate email tasks with Vercel AI SDK

Build interfaces that let your agents act on emails instantly. When a user needs to move a task forward, the system triggers `create_gmelius_card` to update your Kanban boards from within the browser. Efficiency gains come from direct manipulation. You don't need to bounce between tabs because `list_gmelius_templates` keeps your team's standard responses ready for the AI to insert.

Verify Gmelius status in Vercel AI SDK

Keep your application stable by checking the connection before running heavy tasks. Use `check_gmelius_status` as a pre-flight call to ensure the API is responsive. This prevents errors during live user sessions. If the status call fails, you can gracefully handle the interruption in your UI components.

Setup guide

Set up Gmelius 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 Gmelius 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 Gmelius transactions",
});

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

Get your connection token →

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Why Choose Vinkius

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Real-time monitoring

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visibility into every interaction

Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

60%

lower AI costs

Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

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

Common questions about Gmelius MCP in Vercel AI SDK

Yes. You can stream board data directly into your frontend components. Use the MCP tools to fetch live stats and display them in your application.

It does. The tools are designed to work with streaming responses. You get data back as soon as the server processes the request.

You pass the tool definitions to your agent. When the agent decides an action is needed, it calls the corresponding tool like `create_gmelius_card`.

You are bound by the API response limits. We recommend using pagination where possible when you `list_gmelius_conversations`.

Your email content and board metadata remain private. We use secure endpoints and your provided token to keep every request isolated.

Use it with your favorite AI tools

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