Trengo MCP Server for Vercel AI SDKGive Vercel AI SDK instant access to 12 tools to Create Ticket, Create Webhook, Get Account Profile, and more
The Vercel AI SDK is the TypeScript toolkit for building AI-powered applications. Connect Trengo 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 Trengo app connector for Vercel AI SDK is a standout in the Communication Messaging category — giving your AI agent 12 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 Trengo, 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 Trengo MCP Server
Connect your Trengo omnichannel inbox to any AI agent and simplify how you manage customer conversations, team collaboration, and support tickets through natural conversation.
The Vercel AI SDK gives every Trengo tool full TypeScript type inference, IDE autocomplete, and compile-time error checking. Connect 12 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
- Unified Inbox Management — List all tickets and conversations across WhatsApp, Email, and Chat in one place.
- Ticket Control — Create new support tickets, update statuses (OPEN, CLOSED, ASSIGNED), and manage assignments via AI.
- Omichannel Messaging — Send messages to customers or add internal team notes to any conversation.
- Contact & Channel Directory — List your customer database and verify all configured communication channels.
- Team Coordination — Query team member lists to understand availability and workload.
- Event Monitoring — List and create webhooks to track conversation events in real-time.
The Trengo MCP Server exposes 12 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 12 Trengo tools available for Vercel AI SDK
When Vercel AI SDK connects to Trengo through Vinkius, your AI agent gets direct access to every tool listed below — spanning omnichannel-inbox, helpdesk-ticketing, shared-inbox, 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.
Create a new ticket
Create a new webhook
Get current user profile
Get ticket details
). List communication channels
List all contacts
List ticket messages
List team users
List all support tickets
List configured webhooks
Send a message
Update ticket status
Connect Trengo to Vercel AI SDK via MCP
Follow these steps to wire Trengo 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 Trengo MCP Server
Vercel AI SDK provides unique advantages when paired with Trengo 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 Trengo integration everywhere
Built-in streaming UI primitives let you display Trengo 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
Trengo + Vercel AI SDK Use Cases
Practical scenarios where Vercel AI SDK combined with the Trengo MCP Server delivers measurable value.
AI-powered web apps: build dashboards that query Trengo in real-time and stream results to the UI with zero loading states
API backends: create serverless endpoints that orchestrate Trengo tools and return structured JSON responses to any frontend
Chatbots with tool use: embed Trengo capabilities into conversational interfaces with streaming responses and tool call visibility
Internal tools: build admin panels where team members interact with Trengo through natural language queries
Example Prompts for Trengo in Vercel AI SDK
Ready-to-use prompts you can give your Vercel AI SDK agent to start working with Trengo immediately.
"List all currently open support tickets."
"Show me the last 3 messages for ticket #88231."
"Close ticket #10293 as 'CLOSED' and add a note 'Resolved via AI'."
Troubleshooting Trengo MCP Server with Vercel AI SDK
Common issues when connecting Trengo to Vercel AI SDK through the Vinkius, and how to resolve them.
createMCPClient is not a function
npm install @ai-sdk/mcpTrengo + Vercel AI SDK FAQ
Common questions about integrating Trengo 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.