Custify MCP Server for Vercel AI SDKGive Vercel AI SDK instant access to 8 tools to Create Person, Get Company Details, Get Person Details, and more
The Vercel AI SDK is the TypeScript toolkit for building AI-powered applications. Connect Custify 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 Custify app connector for Vercel AI SDK is a standout in the Productivity category — giving your AI agent 8 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 Custify, 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 Custify MCP Server
Connect your Custify customer success account to any AI agent and simplify how you manage your product users, track account health, and monitor churn risk through natural conversation.
The Vercel AI SDK gives every Custify tool full TypeScript type inference, IDE autocomplete, and compile-time error checking. Connect 8 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
- User & Company Oversight — List all managed people and organizations and retrieve detailed metadata and health scores.
- Health Monitoring — Query health score metrics and values to identify at-risk customers and churn signals instantly.
- Event Tracking — Record custom user actions and events programmatically to feed your success analytics.
- Segment Analysis — List and query defined customer segments to understand your user distribution.
- CRM Control — Create new person records and update profile data directly via AI commands.
- Engagement Insights — Fetch engagement history and metadata for individual accounts directly from the agent.
The Custify MCP Server exposes 8 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 8 Custify tools available for Vercel AI SDK
When Vercel AI SDK connects to Custify through Vinkius, your AI agent gets direct access to every tool listed below — spanning customer-success, health-score, churn-prevention, 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 person record
Get details for a specific company
Get details for a specific person
List customer companies
List customer health scores
List product users (people)
List user segments
Track a custom event
Connect Custify to Vercel AI SDK via MCP
Follow these steps to wire Custify 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 Custify MCP Server
Vercel AI SDK provides unique advantages when paired with Custify 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 Custify integration everywhere
Built-in streaming UI primitives let you display Custify 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
Custify + Vercel AI SDK Use Cases
Practical scenarios where Vercel AI SDK combined with the Custify MCP Server delivers measurable value.
AI-powered web apps: build dashboards that query Custify in real-time and stream results to the UI with zero loading states
API backends: create serverless endpoints that orchestrate Custify tools and return structured JSON responses to any frontend
Chatbots with tool use: embed Custify capabilities into conversational interfaces with streaming responses and tool call visibility
Internal tools: build admin panels where team members interact with Custify through natural language queries
Example Prompts for Custify in Vercel AI SDK
Ready-to-use prompts you can give your Vercel AI SDK agent to start working with Custify immediately.
"List all active companies in my Custify account."
"Show me the details and health for person 'john.doe@example.com'."
"Track a 'Button Clicked' event for user 'user_88231'."
Troubleshooting Custify MCP Server with Vercel AI SDK
Common issues when connecting Custify to Vercel AI SDK through the Vinkius, and how to resolve them.
createMCPClient is not a function
npm install @ai-sdk/mcpCustify + Vercel AI SDK FAQ
Common questions about integrating Custify 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.