How to Use the LiftedWork MCP in Mastra AI

Q: Can Mastra AI handle conditional branching based on LiftedWork data?

Yes. You can use the output of listtimeentries to trigger conditional steps, such as generating an invoice when a candidate's logged hours exceed a specific threshold.

Q: How does LiftedWork integrate with Mastra AI's human-in-the-loop system?

You can set approval flags on high-impact tools like createproject. This gives you fine-grained control over how the MCP Server modifies your database.

Build resilient, automated hiring pipelines by connecting LiftedWork tools to your Mastra AI workflows.

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Connect LiftedWork MCP to Mastra AI

Create your Vinkius account to connect LiftedWork 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 LiftedWork with Mastra AI

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Automatic task creation and retries

The `create_task` tool inserts new agency assignments and candidate milestones into your active tracking queues. Mastra AI wraps this tool in a workflow engine that automatically retries the operation if your database experiences transient network hiccups. If a task fails to register, the system pauses, retries, and won't escalate to a human operator until three attempts fail. You can configure these exponential backoff rules directly in TypeScript.

Branching workflows for client onboarding

The `list_clients` tool retrieves active hiring organizations to determine where to route new job seeker profiles. This MCP Server lets your Mastra agent branch its logic depending on whether a client already exists in your database. If the client is missing, the agent triggers a conditional branch to register them before running `create_project`. We do this to keep your database clean and prevent orphaned project records.

Coordinate recruitment with Mastra AI agents

The `list_projects` and `list_tasks` tools expose the full scope of active job placements and candidate pipelines. Mastra AI agents use these tools to audit open roles and assign follow-up tasks without manual intervention. Developers can define strict human-in-the-loop approvals for sensitive MCP tools. For instance, you can require a recruiter to approve a project before the agent executes `create_project`.

Setup guide

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

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

const result = await agent.generate(
  "List recent LiftedWork 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 LiftedWork. 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 LiftedWork MCP in Mastra AI

Instantiate the client with the Vinkius URL to connect the MCP Server. Fetch the tool definitions using `mcpClient.listTools()` and spread them directly into your agent configuration.

Yes. You can use the output of `list_time_entries` to trigger conditional steps, such as generating an invoice when a candidate's logged hours exceed a specific threshold.

You can set approval flags on high-impact tools like `create_project`. This gives you fine-grained control over how the MCP Server modifies your database.

The client automatically detects the transport layer. It defaults to Server-Sent Events (SSE) over HTTP, providing a lightweight channel for your MCP Server operations.

Mastra AI communicates with Vinkius over encrypted HTTPS channels. No task descriptions or project scopes are cached, and the execution environment is destroyed immediately after your agent finishes its run.

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