How to Use the Lancerkit MCP in Mastra AI

Build resilient billing workflows in Mastra AI by automating Lancerkit operations with built-in retry logic and failure handling.

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Connect Lancerkit MCP to Mastra AI

Create your Vinkius account to connect Lancerkit 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 Lancerkit with Mastra AI

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Automated billing workflows

Trigger invoice generation based on time logs. Your agent uses `list_projects` and `get_time_logs` to calculate totals without manual input. If a request fails, the Mastra AI engine automatically retries. This ensures your billing pipeline keeps moving even when network blips happen.

Conditional invoice dispatch

Set up branching logic based on `get_status` and `list_invoices` results. Your agent can decide to pause or proceed based on account health. This prevents errors before they reach your clients. You define the rules, and the agent executes them reliably every time.

Multi-step sync operations

Chain together `get_client` and `list_services` to sync your database with external records. Your agent validates the data through every step. It handles complex dependencies that usually break simple scripts. You get a robust process that handles edge cases gracefully.

Setup guide

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

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

const result = await agent.generate(
  "List recent Lancerkit 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 Lancerkit. 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

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

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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 Lancerkit MCP in Mastra AI

Use the MCPClient class in your project. Add the URL provided by Vinkius, and you can immediately spread the tools into your agent definition.

Yes, the agent framework manages retries. If a tool call to `get_invoice` times out, Mastra AI handles the backoff logic automatically.

You can set requireToolApproval for any sensitive operation. This forces the agent to wait for your sign-off before sending an invoice.

It is fully compatible. You can treat these tools as native steps in your agent pipeline to automate your entire freelance admin stack.

All your sensitive time logs and client metadata remain isolated. The server uses ephemeral sessions, so no persistent data stays on the agent's memory.

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