How to Use the Kentico (CMS & DXP) MCP in Mastra AI

Q: How are custom tables queried in Mastra AI?

Use listcustomtablerows to pull data into your agent's memory. You can then process this data within your agent's internal logic steps.

Build resilient Kentico (CMS & DXP) workflows in Mastra AI with automatic retries and conditional branching.

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Connect Kentico (CMS & DXP) MCP to Mastra AI

Create your Vinkius account to connect Kentico (CMS & DXP) 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.

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Setup Kentico (CMS & DXP) with Mastra AI

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Workflow-driven Kentico (CMS & DXP) actions

Integrate Kentico operations into your agent's decision tree. If an `update_site_document` call fails due to a network blip, Mastra AI handles the retry logic automatically. This ensures your content updates succeed even when the connection is unstable. You define the flow, and the framework manages the execution state.

Granular object lifecycle management

Control your system objects with programmatic precision. Use `delete_system_object` or `get_single_object` inside your multi-step pipelines to clean up or verify resources. This is ideal for automated environment teardowns or dynamic resource provisioning. Your agents act as the gatekeepers for your configuration.

Automated audit and reporting

Fetch metrics from your custom tables with `list_custom_table_rows` and pipe them into your monitoring agents. You can trigger alerts if specific row values exceed your thresholds. This turns your CMS into a live telemetry source. Your agent monitors the state and acts whenever the data deviates from your rules.

Setup guide

Set up Kentico (CMS & DXP) 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 Kentico (CMS & DXP) 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: "kentico-cms-dxp-mcp-client",
  servers: {
    "kentico-cms-dxp-mcp": {
      url: new URL(
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
      ),
    },
  },
});

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

const result = await agent.generate(
  "List recent Kentico (CMS & DXP) transactions"
);
console.log(result.text);

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Common questions about Kentico (CMS & DXP) MCP in Mastra AI

You register the server in your Mastra agent definition. Once initialized, the tools appear in your agent's available toolset for use in any workflow step.

Yes. You can configure conditional branches in your workflow to handle failures from `create_system_object` or other write operations.

Absolutely. Use the requireToolApproval flag for sensitive operations like deletions. The agent pauses until a human signs off on the action.

Use `list_custom_table_rows` to pull data into your agent's memory. You can then process this data within your agent's internal logic steps.

Vinkius isolates every session. The server acts as an authenticated proxy, ensuring only authorized agents can read or write your sensitive configuration data.

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