How to Use the Planhat MCP in Mastra AI

Q: How does this server handle Planhat PII data?

The server transmits raw data from fields like listplanhatendusers only when requested by the agent. You control which tools are exposed, limiting access to sensitive customer identification data.

Build resilient customer success workflows for Mastra AI using the Planhat MCP Server.

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Connect Planhat MCP to Mastra AI

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Setup Planhat with Mastra AI

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Automated renewal intervention logic

Create conditional workflows in Mastra that react to `list_planhat_licenses` updates. If a license is expiring, your agent automatically flags the account for review. Stop manual tracking of renewals. By linking `list_planhat_tasks` to your agent's decision engine, you ensure that no critical customer touchpoint is ever missed again.

Multi-step account audit sequences

Chain together `get_planhat_company` and `list_planhat_conversations` to build a full audit trail for your CSMs. Mastra handles the branching logic if information is missing. Your agents can now perform deep dives into account health. If the data from `list_planhat_notes` shows negative sentiment, the workflow triggers an immediate alert to the account manager.

Graceful failure handling for CS ops

Use the Mastra workflow engine to retry failed API calls to the Planhat MCP server. If an endpoint is busy, the agent waits and tries again automatically. Keep your operations running even during spikes. By checking `list_planhat_assets` through a structured Mastra agent, you ensure that hardware or seat counts are accurate before taking action.

Setup guide

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

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

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

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Common questions about Planhat MCP in Mastra AI

Import the MCP client into your Mastra agent configuration. You then spread the available tools into your agent's tool set to give it direct access to Planhat endpoints.

Yes, you can configure retry logic within your Mastra workflows. If a call to `list_planhat_companies` fails, the engine handles the backoff strategy you define.

Mastra maintains strict boundaries for your agents. The Planhat MCP server communicates over a secure tunnel, keeping your customer records within your private execution environment.

Absolutely. Use the requireToolApproval setting in your Mastra agent to pause execution. This is perfect for high-stakes actions like updating a `list_planhat_licenses` record.

The server transmits raw data from fields like `list_planhat_end_users` only when requested by the agent. You control which tools are exposed, limiting access to sensitive customer identification data.

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