How to Use the UKG Pro Workforce Management MCP in Google ADK

Q: How does the Google ADK assist with UKG Pro Workforce Management scheduling?

It exposes the schedules tool directly to your agent. Because it's integrated with BigQuery, you can run historical trend analysis on employee schedules across years of data within your Google Cloud setup.

Q: Can I use the Google ADK for reporting on UKG Pro Workforce Management time-off requests?

Absolutely. You'll call the timeoff tool, and the resulting structured data can be passed to Gemini models. This lets you not only list requests but also analyze patterns in leave usage across departments.

Q: When building an agent for UKG Pro Workforce Management, what kind of data can I expect from the MCP Server?

You'll get four main data types: employee schedules (schedules), timesheets (timesheets), time off requests (timeoff), and current accrual balances (accruals). All are ready for BigQuery analysis.

Connect UKG Pro Workforce Management data to BigQuery using the Google ADK for enterprise insights.

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Connect UKG Pro Workforce Management MCP to Google ADK

Create your Vinkius account to connect UKG Pro Workforce Management to Google ADK 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 UKG Pro Workforce Management with Google ADK

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Reading UKG Pro Schedules and Timesheets

Your agent can pull both planned schedules and actual timesheets. These tools allow your LLM client to see a comprehensive view of employee work patterns using `schedules` and `timesheets`. This data feeds directly into Google Cloud for analysis. The long-context reasoning of Gemini models lets you hold massive datasets, making it easy to compare months of historical labor data from UKG Pro.

Managing Leave Requests and Balances

Need to check an employee's leave status? The agent calls `accruals` for current balances. Then, if necessary, it uses `timeoff` to fetch all associated requests. All this data is structured for BigQuery ingestion. The ability to use Google ADK means you aren't just querying; you're preparing that HR data for deep analytical models.

Building Enterprise Workflows with the MCP Server

The combination of tools—`schedules`, `timesheets`, and `timeoff`—allows your agent to build multi-step workflows. For instance, check time off status, then retrieve historical timesheets for that period. Because this runs on Google Cloud, you can pass all the results into Vertex AI for immediate pattern detection, transforming raw HR data into actionable insights.

Setup guide

Set up UKG Pro Workforce Management MCP in Google ADK

Prerequisites

Python 3.10+ installed
google-adk package (pip install google-adk)
Active Vinkius subscription with a valid endpoint token

1

Install Google ADK

Run pip install google-adk to install the Agent Development Kit. MCP support is included via the McpToolset class.
2

Connect via SSE transport

Use McpToolset.from_server() with SseServerParams pointing to your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Create an LlmAgent

Pass the returned mcp_tools list directly to LlmAgent(tools=mcp_tools). The ADK maps each MCP tool to a native Gemini function call — no manual schema definitions required.
4

Run with any Gemini model

The agent works with any Gemini model (gemini-2.0-flash, gemini-2.5-pro, etc.). Copy the full example on the right to get started with UKG Pro Workforce Management tools in your ADK agent.

agent.py

from google.adk.agents import LlmAgent
from google.adk.tools.mcp_tool.mcp_toolset import McpToolset
from google.adk.tools.mcp_tool.mcp_session_manager import SseServerParams

# Connect to the MCP via SSE
mcp_tools, exit_stack = await McpToolset.from_server(
    connection_params=SseServerParams(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    )
)

# Create your agent with auto-discovered tools
agent = LlmAgent(
    name="UKG Pro Workforce Management_agent",
    model="gemini-2.0-flash",
    instruction="You have access to UKG Pro Workforce Management tools via MCP.",
    tools=mcp_tools,
)

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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 UKG Pro Workforce Management. 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 UKG Pro Workforce Management MCP in Google ADK

It exposes the `schedules` tool directly to your agent. Because it's integrated with BigQuery, you can run historical trend analysis on employee schedules across years of data within your Google Cloud setup.

Absolutely. You'll call the `timeoff` tool, and the resulting structured data can be passed to Gemini models. This lets you not only list requests but also analyze patterns in leave usage across departments.

You get long-context reasoning (1M+ tokens), meaning you can pass huge volumes of data from `timesheets`, `accruals`, and other sources at once. This is perfect for generating comprehensive compliance reports in BigQuery.

It touches employee accrued leave balances, specifically accessing data points like PTO and sick leave totals via the `accruals` tool. This is structured financial/HR data.

You'll get four main data types: employee schedules (`schedules`), timesheets (`timesheets`), time off requests (`timeoff`), and current accrual balances (`accruals`). All are ready for BigQuery analysis.

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