How to Use the Make (Workflow Automation) MCP in Vercel AI SDK

Q: Can I show scenario logs in my Vercel AI SDK dashboard?

Yes. You can use the listscenariologs tool to pull execution history and render it as a list or table directly inside your React components.

Build live-streaming automation dashboards in your Vercel AI SDK app by connecting directly to your Make (Workflow Automation) scenarios.

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Connect Make (Workflow Automation) MCP to Vercel AI SDK

Create your Vinkius account to connect Make (Workflow Automation) 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 Make (Workflow Automation) with Vercel AI SDK

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Real-time scenario monitoring in your UI

Feed live status updates directly into your React or Next.js components. Use `list_scenarios` to pull your active workflows into the frontend and display them as they update. Your users see the state of their automations without waiting for background reloads. It turns static logs into a dynamic part of your application interface.

Debug production failures instantly

Stop digging through the Make dashboard when something breaks. When a component triggers an error, use `list_scenario_logs` to fetch the exact execution details and display them in your app. Your UI can now show the specific error message to the user immediately. It gives you a way to surface technical issues without leaving the browser.

Manage connections and team data

Sync your internal user permissions with your automation environment. Use `list_connections` and `list_teams` to verify that your app has the right access before executing any logic. This keeps your data flow tight and secure. You only show users the scenarios they actually have the rights to manage.

Setup guide

Set up Make (Workflow Automation) 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 Make (Workflow Automation) 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 Make (Workflow Automation) transactions",
});

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

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Make. 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

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Common questions about Make (Workflow Automation) MCP in Vercel AI SDK

Install the MCP client package via npm and initialize it with your Vinkius endpoint. Pass the tools retrieved from the server into your `streamText` function to make them available to your AI agent.

Yes. You can use the `list_scenario_logs` tool to pull execution history and render it as a list or table directly inside your React components.

It does. Since the connection uses standard HTTP transport, you can call these tools from your edge routes to keep your response times fast and your logic decentralized.

Use the built-in authProvider within the MCP client. This ensures your API tokens stay out of your source code while allowing the server to perform actions.

Your data stays isolated within your specific connection. We only touch your scenario configurations and execution logs, and everything is encrypted in transit.

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