VBOUT MCP Server for Vercel AI SDKGive Vercel AI SDK instant access to 9 tools to Add Contact, Add Ecommerce Order, Create Social Post, and more
The Vercel AI SDK is the TypeScript toolkit for building AI-powered applications. Connect VBOUT through Vinkius and every tool is available as a typed function. ready for React Server Components, API routes, or any Node.js backend.
Ask AI about this App Connector for Vercel AI SDK
The VBOUT app connector for Vercel AI SDK is a standout in the Marketing Automation category — giving your AI agent 9 tools to work with, ready to go from day one.
Vinkius delivers Streamable HTTP and SSE to any MCP client
import { createMCPClient } from "@ai-sdk/mcp";
import { generateText } from "ai";
import { openai } from "@ai-sdk/openai";
async function main() {
const mcpClient = await createMCPClient({
transport: {
type: "http",
// Your Vinkius token. get it at cloud.vinkius.com
url: "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
},
});
try {
const tools = await mcpClient.tools();
const { text } = await generateText({
model: openai("gpt-4o"),
tools,
prompt: "Using VBOUT, list all available capabilities.",
});
console.log(text);
} finally {
await mcpClient.close();
}
}
main();
* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
About VBOUT MCP Server
Connect your VBOUT marketing automation account to any AI agent and simplify how you manage your lead lifecycle, multi-channel campaigns, and social presence through natural conversation.
The Vercel AI SDK gives every VBOUT tool full TypeScript type inference, IDE autocomplete, and compile-time error checking. Connect 9 tools through Vinkius and stream results progressively to React, Svelte, or Vue components. works on Edge Functions, Cloudflare Workers, and any Node.js runtime.
What you can do
- Lead Management — List and search contacts, and add new leads to specific email marketing lists instantly.
- Automation Control — Query and trigger marketing automation workflows for specific contacts to scale your engagement.
- Campaign Monitoring — List active and past marketing campaigns to track your commercial efforts.
- Social Scheduling — Create and publish social media posts directly from your workspace via AI commands.
- E-commerce Sync — Log customer orders into VBOUT to power lifecycle marketing and personalized segments.
The VBOUT MCP Server exposes 9 tools through the Vinkius. Connect it to Vercel AI SDK in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
All 9 VBOUT tools available for Vercel AI SDK
When Vercel AI SDK connects to VBOUT through Vinkius, your AI agent gets direct access to every tool listed below — spanning lead-nurturing, campaign-management, social-media-marketing, and more. Every call is secured with network, filesystem, subprocess, and code evaluation entitlements inside a sandboxed runtime. Beyond a simple connection, you get a full AI Gateway with real-time visibility into agent activity, enterprise governance, and optimized token usage.
Requires email and list_id. Add a contact to a list
Add an e-commerce order
Create a social media post
Get contact details
List marketing campaigns
List VBOUT email marketing lists
List automation workflows
Search for contacts
Trigger a workflow for a contact
Connect VBOUT to Vercel AI SDK via MCP
Follow these steps to wire VBOUT into Vercel AI SDK. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.
Install dependencies
npm install @ai-sdk/mcp ai @ai-sdk/openaiReplace the token
[YOUR_TOKEN_HERE] with your Vinkius tokenRun the script
agent.ts and run with npx tsx agent.tsExplore tools
Why Use Vercel AI SDK with the VBOUT MCP Server
Vercel AI SDK provides unique advantages when paired with VBOUT through the Model Context Protocol.
TypeScript-first: every MCP tool gets full type inference, IDE autocomplete, and compile-time error checking out of the box
Framework-agnostic core works with Next.js, Nuxt, SvelteKit, or any Node.js runtime. same VBOUT integration everywhere
Built-in streaming UI primitives let you display VBOUT tool results progressively in React, Svelte, or Vue components
Edge-compatible: the AI SDK runs on Vercel Edge Functions, Cloudflare Workers, and other edge runtimes for minimal latency
VBOUT + Vercel AI SDK Use Cases
Practical scenarios where Vercel AI SDK combined with the VBOUT MCP Server delivers measurable value.
AI-powered web apps: build dashboards that query VBOUT in real-time and stream results to the UI with zero loading states
API backends: create serverless endpoints that orchestrate VBOUT tools and return structured JSON responses to any frontend
Chatbots with tool use: embed VBOUT capabilities into conversational interfaces with streaming responses and tool call visibility
Internal tools: build admin panels where team members interact with VBOUT through natural language queries
Example Prompts for VBOUT in Vercel AI SDK
Ready-to-use prompts you can give your Vercel AI SDK agent to start working with VBOUT immediately.
"List all my email marketing lists in VBOUT."
"Add 'John Doe' (john@example.com) to the 'Webinar Leads' list."
"Post this to my social media: 'Join our upcoming MCP webinar! https://vinkius.com/live'"
Troubleshooting VBOUT MCP Server with Vercel AI SDK
Common issues when connecting VBOUT to Vercel AI SDK through the Vinkius, and how to resolve them.
createMCPClient is not a function
npm install @ai-sdk/mcpVBOUT + Vercel AI SDK FAQ
Common questions about integrating VBOUT MCP Server with Vercel AI SDK.
How does the Vercel AI SDK connect to MCP servers?
createMCPClient from @ai-sdk/mcp and pass the server URL. The SDK discovers all tools and provides typed TypeScript interfaces for each one.Can I use MCP tools in Edge Functions?
Does it support streaming tool results?
useChat and streamText that handle tool calls and display results progressively in the UI.