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Kavkom MCP Server for Vercel AI SDKGive Vercel AI SDK instant access to 7 tools to Create Contact, Get Call Details, List Calls, and more

Built by Vinkius GDPR 7 Tools SDK

The Vercel AI SDK is the TypeScript toolkit for building AI-powered applications. Connect Kavkom 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 Kavkom app connector for Vercel AI SDK is a standout in the Customer Support category — giving your AI agent 7 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 Kavkom, list all available capabilities.",
    });
    console.log(text);
  } finally {
    await mcpClient.close();
  }
}

main();
Kavkom
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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 Kavkom MCP Server

Connect your Kavkom account to any AI agent and manage phone communications through natural conversation.

The Vercel AI SDK gives every Kavkom tool full TypeScript type inference, IDE autocomplete, and compile-time error checking. Connect 7 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

  • Contact Management — List and inspect contacts with call history
  • Call Logs — Browse call history with duration, direction, and status
  • Phone Lines — List available phone lines and their assignments
  • Voicemail — Access voicemail messages with transcripts
  • Call Recordings — Retrieve and review call recordings

The Kavkom MCP Server exposes 7 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 7 Kavkom tools available for Vercel AI SDK

When Vercel AI SDK connects to Kavkom through Vinkius, your AI agent gets direct access to every tool listed below — spanning cloud-telephony, ivr, call-routing, 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_contact

Add a new contact

get_call_details

Get details for a specific call

list_calls

List Kavkom call history

list_crm_contacts

List synced contacts

list_sms_history

List sent and received SMS

list_team_members

List account users

send_sms_message

Send an SMS message

Connect Kavkom to Vercel AI SDK via MCP

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

01

Install dependencies

Run npm install @ai-sdk/mcp ai @ai-sdk/openai
02

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token
03

Run the script

Save to agent.ts and run with npx tsx agent.ts
04

Explore tools

The SDK discovers 7 tools from Kavkom and passes them to the LLM

Why Use Vercel AI SDK with the Kavkom MCP Server

Vercel AI SDK provides unique advantages when paired with Kavkom through the Model Context Protocol.

01

TypeScript-first: every MCP tool gets full type inference, IDE autocomplete, and compile-time error checking out of the box

02

Framework-agnostic core works with Next.js, Nuxt, SvelteKit, or any Node.js runtime. same Kavkom integration everywhere

03

Built-in streaming UI primitives let you display Kavkom tool results progressively in React, Svelte, or Vue components

04

Edge-compatible: the AI SDK runs on Vercel Edge Functions, Cloudflare Workers, and other edge runtimes for minimal latency

Kavkom + Vercel AI SDK Use Cases

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

01

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

02

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

03

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

04

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

Example Prompts for Kavkom in Vercel AI SDK

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

01

"Show today's call log and any pending voicemails."

02

"List all contacts and the phone lines assigned to the team."

03

"Show call recordings from this week for the sales line."

Troubleshooting Kavkom MCP Server with Vercel AI SDK

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

01

createMCPClient is not a function

Install: npm install @ai-sdk/mcp

Kavkom + Vercel AI SDK FAQ

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

01

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.
02

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.
03

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.