How to Use the Appbot MCP in Mastra AI

Build automated customer support workflows in Mastra AI using direct Appbot data connections.

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Works with every AI agent you already use

…and any MCP-compatible client

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Connect Appbot MCP to Mastra AI

Create your Vinkius account to connect Appbot 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 Appbot with Mastra AI

Ask AI about this MCP

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Claude

Perplexity

Automated review monitoring in Mastra AI

Set up an agent to run `list_reviews` on a schedule and branch logic based on the output. If a negative sentiment score appears, your workflow triggers an alert immediately. This MCP Server provides the raw data your agent needs to decide whether to escalate a ticket. You remove the manual check from your support loop.

Multi-step feedback processing

Chain multiple tools like `list_apps` and `get_review_details` to gather context before your agent drafts a response. You handle complex feedback cycles without writing custom scrapers. Your Mastra AI agents use these tools to build a full picture of the user complaint. The workflow engine manages the retries if the connection drops.

Custom topic tracking for agents

Define specific issues in your dashboard and use `get_reviews_by_custom_topic` to feed those into your agent's reasoning. Your agents focus only on the topics that matter to your business. It handles the heavy lifting of sorting through thousands of reviews. Your agent just gets the high-priority data points it needs to act.

Setup guide

Set up Appbot 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 Appbot 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: "appbot-mcp-client",
  servers: {
    "appbot-mcp": {
      url: new URL(
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
      ),
    },
  },
});

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

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

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Why Choose Vinkius

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

Connect Appbot 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 Appbot MCP in Mastra AI

Add the server URL to your agent configuration. Mastra AI will automatically discover the tools and allow you to call them within your workflow steps.

Yes, you can use the sentiment results from the tools to drive logic. If the sentiment is low, the agent can route to a human support queue.

The connection is stable and designed for automated agents. If a call fails, the framework handles the retry logic for you.

You can set tool approval to true. This forces the agent to ask you before it performs sensitive actions like pulling account details.

Your review content is handled in an ephemeral sandbox. No raw credentials or sensitive customer PII persist in the workflow memory after the job finishes.

Use it with your favorite AI tools

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