How to Use the KeyPay MCP in Mastra AI

Q: How do I configure Mastra AI to use KeyPay?

Install @mastra/mcp and instantiate a new MCPClient. Provide your Vinkius server URL in the servers object. Call listTools() and assign them to your agent.

Q: Does Mastra AI support human approval for KeyPay actions?

It does. You can set requireToolApproval on specific actions. A manager can review the data before the agent processes a pay run.

Build resilient payroll workflows with KeyPay and Mastra AI using conditional branching and automatic retries.

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Connect KeyPay MCP to Mastra AI

Create your Vinkius account to connect KeyPay 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 KeyPay with Mastra AI

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Perplexity

Automate leave approvals via the KeyPay MCP Server

The `list_leave_requests` tool grabs pending time-off entries from the system. Your agent evaluates each request against company policy. Mastra AI shines when things break. If the API times out during the fetch, the framework automatically triggers an exponential backoff. Your workflow eventually succeeds without manual intervention.

Audit pay run deductions and earnings

Combine `list_pay_run_deductions` and `list_pay_run_earnings` to verify payroll accuracy before finalization. The workflow pulls both datasets and compares the totals. You can build conditional branches based on the results. If the deductions exceed a specific threshold, Mastra routes the workflow to a human-in-the-loop approval step. Otherwise, it proceeds to the next node.

Sync employee directories reliably

Running `list_employees` and `get_employee_details` pulls the entire staff roster into your local database. The tools handle the exact data structures required by the API. Deploying this sync job takes one command. You define the Mastra agent, spread the MCP tools into its configuration, and push it to your cloud provider.

Setup guide

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

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

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

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by KeyPay. 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.

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Common questions about KeyPay MCP in Mastra AI

Install `@mastra/mcp` and instantiate a new `MCPClient`. Provide your Vinkius server URL in the servers object. Call `listTools()` and assign them to your agent.

They absolutely can. The framework includes built-in retry logic. If the KeyPay server throws a rate limit error, your workflow pauses and tries again automatically.

It does. You can set `requireToolApproval` on specific actions. A manager can review the data before the agent processes a pay run.

The client auto-detects the transport layer. You pass the HTTP URL, and it connects via Streamable HTTP or SSE based on the endpoint configuration.

Ephemeral execution keeps your information safe. When pulling sensitive payloads from `get_employee_details`, the container exists only for the duration of the call. Nothing persists on disk after the connection closes.

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