Can I manually start a retention flow for a customer via AI?

Yes! Use the `start_flow` tool and provide the Flow ID, Customer ID, and Subscription ID. This will initialize the retention experience for that user immediately.

How do I see if a customer successfully stayed after a flow?

Run the `get_flow_session` query with the specific Session ID. It will return the outcome and status of the retention attempt.

Is it possible to update a subscription's status via AI?

Absolutely. Use the `update_subscription` tool by providing the Subscription ID and the new status to synchronize data between your systems and Upzelo.

INSTANT PLUG AND PLAY

Upzelo MCP Server for Vercel AI SDKGive Vercel AI SDK instant access to 10 tools to Get Customer, Get Flow, Get Flow Session, and more

Name: Upzelo
Availability: InStock
Author: Vinkius

Built by Vinkius GDPR 10 Tools SDK

The Vercel AI SDK is the TypeScript toolkit for building AI-powered applications. Connect Upzelo through Vinkius and every tool is available as a typed function. ready for React Server Components, API routes, or any Node.js backend.

Use with Your AI Agent

Ask AI about this App Connector for Vercel AI SDK

Open in ChatGPT Open in Claude Open in Perplexity

The Upzelo app connector for Vercel AI SDK is a standout in the Sales Automation category — giving your AI agent 10 tools to work with, ready to go from day one.

Vinkius delivers Streamable HTTP and SSE to any MCP client

typescript

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 Upzelo, list all available capabilities.",
    });
    console.log(text);
  } finally {
    await mcpClient.close();
  }
}

main();

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Stream every event to Splunk, Datadog, or your own webhook in real-time

* 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 Upzelo MCP Server

Connect your Upzelo churn management account to any AI agent and simplify how you retain customers and manage subscription lifecycles through natural conversation.

The Vercel AI SDK gives every Upzelo tool full TypeScript type inference, IDE autocomplete, and compile-time error checking. Connect 10 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

Customer Management — List and search customer records, and update profile data for better segmentation and targeting.
Retention Flows — List available flows and manually trigger retention sequences for customers at risk of cancelling.
Subscription Tracking — Query all tracked subscriptions and update statuses or trial details programmatically.
Flow Monitoring — Check the real-time status and outcomes of active flow sessions to verify retention success.
External ID Sync — Link your internal system identifiers to Upzelo customer records for seamless integration.

The Upzelo MCP Server exposes 10 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 10 Upzelo tools available for Vercel AI SDK

When Vercel AI SDK connects to Upzelo through Vinkius, your AI agent gets direct access to every tool listed below — spanning churn-reduction, subscription-management, customer-retention, 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.

get_customer

Get details for a specific customer

get_flow

Get details for a specific flow

get_flow_session

Check the status of a flow session

get_subscription

Get details for a specific subscription

list_customers

List all customers in Upzelo

list_flows

List all retention flows

list_subscriptions

List all subscriptions

save_customer

Used for segmentation and targeting. Create or update a customer record

start_flow

Initialize a flow for a customer

update_subscription

Update subscription attributes

Connect Upzelo to Vercel AI SDK via MCP

Follow these steps to wire Upzelo into Vercel AI SDK. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.

Install dependencies

Run npm install @ai-sdk/mcp ai @ai-sdk/openai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the script

Save to agent.ts and run with npx tsx agent.ts

Explore tools

The SDK discovers 10 tools from Upzelo and passes them to the LLM

Why Use Vercel AI SDK with the Upzelo MCP Server

Vercel AI SDK provides unique advantages when paired with Upzelo 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 Upzelo integration everywhere

Built-in streaming UI primitives let you display Upzelo 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

Upzelo + Vercel AI SDK Use Cases

Practical scenarios where Vercel AI SDK combined with the Upzelo MCP Server delivers measurable value.

AI-powered web apps: build dashboards that query Upzelo in real-time and stream results to the UI with zero loading states

API backends: create serverless endpoints that orchestrate Upzelo tools and return structured JSON responses to any frontend

Chatbots with tool use: embed Upzelo capabilities into conversational interfaces with streaming responses and tool call visibility

Internal tools: build admin panels where team members interact with Upzelo through natural language queries

Example Prompts for Upzelo in Vercel AI SDK

Ready-to-use prompts you can give your Vercel AI SDK agent to start working with Upzelo immediately.

"List all customers currently tracked in Upzelo."

"Trigger the 'Basic Retention' flow (ID: fl_8823) for customer 'cust_1029'."

"Show me the details for subscription 'sub_12903'."

Troubleshooting Upzelo MCP Server with Vercel AI SDK

Common issues when connecting Upzelo to Vercel AI SDK through the Vinkius, and how to resolve them.

createMCPClient is not a function

Install: npm install @ai-sdk/mcp

Upzelo + Vercel AI SDK FAQ

Common questions about integrating Upzelo MCP Server with Vercel AI SDK.

How does the Vercel AI SDK connect to MCP servers?

Import 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?

Yes. The AI SDK is fully edge-compatible. MCP connections work on Vercel Edge Functions, Cloudflare Workers, and similar runtimes.

Does it support streaming tool results?

Yes. The SDK provides streaming primitives like useChat and streamText that handle tool calls and display results progressively in the UI.