How to Use the Kustomer MCP in Mastra AI

Q: How do I add the Kustomer MCP to Mastra AI?

Run npm install @mastra/mcp@latest. Instantiate the MCPClient with your server URL, then call listTools() and spread the results into your agent's tool array.

Q: Does Mastra AI support human-in-the-loop for Kustomer actions?

Yes. You can flag specific tools with requireToolApproval. If your agent decides to pull sensitive records, execution pauses until a manager approves the action.

Build resilient support workflows with Mastra AI. Handle Kustomer API failures with built-in retries.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect Kustomer MCP to Mastra AI

Create your Vinkius account to connect Kustomer to Mastra AI and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

GDPR Free for Subscribers

Setup Kustomer with Mastra AI

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Write Mastra AI workflows for Kustomer routing.

This MCP Server plugs directly into your Mastra agent tools so you can run `list_support_conversations` without fearing API timeouts. Support APIs fail. Rate limits trigger. You need a system that doesn't panic when an endpoint drops. Set up a workflow that hits the queue every five minutes. If Kustomer drops the connection, your framework's exponential backoff kicks in automatically. Once the data flows, your logic routes the tickets.

Audit agent workloads with conditional logic.

Build an agent that maps out your entire support floor by pulling your team roster with `list_kustomer_agents`. You want to know exactly who is handling what. Start by pulling your roster and feeding it into your workflow state. From there, branch your workflow. If an agent has too many open tickets, trigger `list_support_queues` to find an alternative department. The agent reassigns the load based on real-time capacity. You write the rules, Mastra executes them.

Dig into timelines without breaking production.

Give your agent the `search_kustomer_timeline` tool and let it hunt through deep customer audits. Audits usually require messy scripts. Now you just give your agent the tool and let it run. Before running heavy queries, your workflow can ping `check_kustomer_api_status` to ensure the platform is healthy. If the status is green, it proceeds to fetch the exact history via `get_conversation_details`. Safe, predictable execution.

Setup guide

Set up Kustomer MCP in Mastra AI

Prerequisites

Node.js 18+ and a TypeScript project
@mastra/mcp + @mastra/core packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run npm install @mastra/mcp @mastra/core plus your preferred model provider (e.g. @ai-sdk/openai).
2

Configure the MCPClient
Create an MCPClient with your Vinkius endpoint as a URL object. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Discover and inject tools
Call mcpClient.listTools() and spread the result into your agent's tools object. All Kustomer tools become native Mastra tools.
4

Run with any model
Swap openai("gpt-4o") for any AI SDK-compatible provider. Call agent.generate() and the agent routes tool calls through MCP automatically.

agent.ts

import { MCPClient } from "@mastra/mcp";
import { Agent } from "@mastra/core/agent";
import { openai } from "@ai-sdk/openai";

const mcpClient = new MCPClient({
  id: "kustomer-mcp-client",
  servers: {
    "kustomer-mcp": {
      url: new URL(
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
      ),
    },
  },
});

const agent = new Agent({
  name: "Kustomer Agent",
  model: openai("gpt-4o"),
  instructions: "You have access to Kustomer tools.",
  tools: {
    ...(await mcpClient.listTools()),
  },
});

const result = await agent.generate(
  "List recent Kustomer transactions"
);
console.log(result.text);

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Kustomer. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

Why Choose Vinkius

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

Connect Kustomer now

Real-time monitoring

Live

visibility into every interaction

Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

60%

lower AI costs

Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about Kustomer MCP in Mastra AI

Run `npm install @mastra/mcp@latest`. Instantiate the `MCPClient` with your server URL, then call `listTools()` and spread the results into your agent's tool array.

Yes. You can flag specific tools with `requireToolApproval`. If your agent decides to pull sensitive records, execution pauses until a manager approves the action.

The framework handles retries natively. If a call fails due to traffic spikes, the agent waits and tries again using exponential backoff.

Create sequential steps in your workflow definition. Step one runs `get_customer_profile`. Pass that output to step two, which fires `list_conversation_messages` for that specific user ID.

The integration accesses custom data classes, chat transcripts, and profile metadata. Vinkius enforces a zero-trust architecture where the token only lives for the duration of the request. Once the workflow step completes, the sandbox is wiped clean.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

OpenAI Agents SDK sdk-python

Google ADK sdk-python

Pydantic AI sdk-python

Vercel AI SDK sdk-typescript