How to Use the Domo MCP in Vercel AI SDK

Q: How do I stream Domo user creation states using the Vercel AI SDK?

You call mcpClient.tools() to fetch the tools from this MCP Server, then pass them to streamText. When the agent runs createuser, the tool execution state is piped directly to your React frontend, allowing you to render custom UI nodes as the user is being registered.

Q: What is the cleanest way to handle Domo API errors in Vercel AI SDK?

Wrap your streamText call in a standard try-catch block and monitor the tool execution stream. If updateuser fails due to an invalid email format, the SDK captures the raw API error from the MCP Server and lets you display a helpful correction prompt to the operator.

Q: Do I need to clean up the connection after executing Domo tools?

Yes, always call mcpClient.close() once your stream finishes. This releases the transport resources and prevents dangling connections on your serverless instances when running commands like deleteuser or removeuserfromgroup.

Watch your AI client build Domo groups and invite users in real-time using the Vercel AI SDK.

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Setup Domo with Vercel AI SDK

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Vercel AI SDK live updates during Domo onboarding

The `create_user` tool lets your Vercel AI SDK application trigger instant Domo user creation without making operators stare at a blank spinner. The moment the Domo API accepts the registration, the new profile pops onto the screen in real-time. It means zero UI lag when firing off Domo invites. Your Vercel AI SDK frontend streams the raw output from `create_user` directly into a React component. The operator gets immediate confirmation that the Domo invitation email went out, making the admin panel feel incredibly fast.

Direct client-side Domo group assignments

The `add_user_to_group` tool allows your Vercel AI SDK application to manage Domo team access directly inside your interactive dashboard. The client handles the execution on Edge Functions, keeping your backend footprint light. You can let your Vercel AI SDK agent look at a user's role and immediately run `create_group` if the requested Domo department does not exist yet. The interface updates as each step executes, showing the exact relationship being built between the user and the Domo group.

Instant feedback on Domo account cleanup

The `delete_user` and `remove_user_from_group` tools ensure that offboarding Domo users happens with instant, streamable confirmation. When your agent invokes these actions through this MCP Server, the Vercel AI SDK streams the success payload straight to your admin console. This setup avoids the typical black-box execution of traditional Domo admin scripts. If the Domo API throws a rate limit or a failure while executing `update_user` during a role change, the Vercel AI SDK streams the error directly to the browser. Your admin can intervene before security gaps persist.

Setup guide

Set up Domo 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 Domo 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 Domo transactions",
});

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

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Common questions about Domo MCP in Vercel AI SDK

You call `mcpClient.tools()` to fetch the tools from this MCP Server, then pass them to `streamText`. When the agent runs `create_user`, the tool execution state is piped directly to your React frontend, allowing you to render custom UI nodes as the user is being registered.

Yes, this MCP Server is compatible with edge runtimes. You can execute `create_group` and `add_user_to_group` inside Next.js Edge Routes by establishing an HTTP transport connection to the Vinkius managed endpoint.

Wrap your `streamText` call in a standard try-catch block and monitor the tool execution stream. If `update_user` fails due to an invalid email format, the SDK captures the raw API error from the MCP Server and lets you display a helpful correction prompt to the operator.

Yes, always call `mcpClient.close()` once your stream finishes. This releases the transport resources and prevents dangling connections on your serverless instances when running commands like `delete_user` or `remove_user_from_group`.

All Domo user emails, names, and group memberships are processed within an isolated V8 sandbox. Vinkius handles the underlying credential storage, meaning your Vercel AI SDK code never directly handles raw API keys or administrative master tokens during user creation.

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