How to Use the UKG Ready MCP in Google ADK

Q: How do I use the Google ADK to analyze UKG Ready payroll history?

You expose the payroll toolset via your McpToolset. The agent then calls this tool, pulling historical data that Gemini models can process in their large context window for deep analysis.

Q: Can I list timesheets and employee info using UKG Ready with Google ADK?

Yes. You pass the timesheets and employees tools to your LlmAgent. This setup allows your agents to pull granular time data and compare it against core personnel records.

Q: Does the Google ADK support listing job applicants from UKG Ready?

The agent uses the exposed applicants tool for this function. It reads candidate lists directly from UKG Ready, allowing your enterprise agents to manage recruitment pipelines alongside active employees.

Build enterprise agents acting on UKG Ready data using Google ADK.

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Connect UKG Ready MCP to Google ADK

Create your Vinkius account to connect UKG Ready 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 Ready with Google ADK

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Ingest and Query Employee Data from UKG Ready

The `employees` tool fetches all current employee details from your UKG Ready instance. These records become available for deep, long-context reasoning within the Gemini models. Since you're building agents on Google Cloud, these structured data points feed directly into BigQuery or Vertex AI. You can correlate this live MCP Server output with other enterprise datasets.

Process Payroll and Timesheet Data in UKG Ready

The agent uses both the `payroll` and `timesheets` tools to gather financial and time-tracking data. You can pass massive amounts of historical data—far beyond typical tool limits—for complex analysis. This is perfect for building auditing agents. The Gemini models hold 1M+ tokens, meaning you won't lose context when analyzing large batches of payroll or timesheet records.

Manage Candidate Data from UKG Ready

Need to check job applicants? Call the `applicants` tool. It pulls all candidate profiles into your agent flow, allowing for immediate review alongside employee data. By integrating this MCP Server with Google Cloud tools, you can build a unified view of talent—from initial application through final employment records.

Setup guide

Set up UKG Ready 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 Ready 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 Ready_agent",
    model="gemini-2.0-flash",
    instruction="You have access to UKG Ready 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 Ready. 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 Ready MCP in Google ADK

You expose the `payroll` toolset via your McpToolset. The agent then calls this tool, pulling historical data that Gemini models can process in their large context window for deep analysis.

Yes. You pass the `timesheets` and `employees` tools to your LlmAgent. This setup allows your agents to pull granular time data and compare it against core personnel records.

The agent uses the exposed `applicants` tool for this function. It reads candidate lists directly from UKG Ready, allowing your enterprise agents to manage recruitment pipelines alongside active employees.

The framework is built for enterprise deployment on Google Cloud. The ability to connect this MCP Server ensures that your agent operates against trusted, live UKG Ready data sources.

The server provides access to applicant lists, current employee records, payroll history, and detailed timesheet logs. All these structured datasets feed into your agent's context.

Use it with your favorite AI tools

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