How to Use the Alpic MCP in Vercel AI SDK

Deploy and monitor your MCP infrastructure directly from your Vercel AI SDK codebase.

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Connect Alpic MCP to Vercel AI SDK

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

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Full lifecycle control for Alpic projects

You can manage your infrastructure without leaving your development environment. Use `create_project` to spin up new instances and `deploy_environment` to push updates to production instantly. Your code handles everything from initial setup to cleanup. When a project is no longer needed, `delete_project` clears the slate, keeping your account organized.

Real-time configuration in Vercel AI SDK

Inject environment variables dynamically using `add_variable` as your application scales. You can audit current settings with `list_variables` to ensure your production keys are correct before streaming responses. These tools let you modify settings on the fly. You'll see the impact immediately when your app consumes the updated configuration.

Monitor performance with Alpic tools

Track the health of your deployments by calling `get_project_analytics`. You get raw data on how your MCP servers perform under load without checking an external dashboard. Debugging becomes a standard function call. `get_deployment_logs` pulls the exact output you need to fix issues, which helps you maintain uptime for your end users.

Setup guide

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

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Common questions about Alpic MCP in Vercel AI SDK

Install the necessary packages and initialize the client with your endpoint URL. You then pass the tools from the server into your generateText calls.

Yes, you can manage them programmatically. Use the variable tools to set and audit your configuration keys directly within your logic.

Your project configuration and environment variables remain isolated. Only your authenticated agent has access to these specific records.

You invoke the log retrieval tool with your project and environment IDs. The output streams right into your terminal or application logs.

You can grab a tunnel ticket to test your setup locally. This lets you verify your integration before you commit to a live deployment.

Use it with your favorite AI tools

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