How to Use the UKG Pro Workforce Management MCP in LlamaIndex
Build knowledge-augmented RAG systems for UKG Pro Workforce Management using LlamaIndex.
Works with every AI agent you already use
…and any MCP-compatible client
Connect UKG Pro Workforce Management MCP to LlamaIndex
Create your Vinkius account to connect UKG Pro Workforce Management to LlamaIndex and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.
Indexing historical time records
When you run the `timesheets` tool, the output gets indexed into your vector store. Now, instead of just viewing a list, you can query past data like, 'What were John's hours on this date?' and get an answer grounded in actual API results.
Searching through time-off policies
Use the `timeoff` tool to pull a list of all employee requests. LlamaIndex indexes these records, letting you ask natural language questions like, 'Who requested PTO next month?' and get results from the knowledge base.
Retrieving schedule conflicts
The `schedules` tool output—staffing patterns for a whole department—becomes searchable. You can combine this with other data to ask, 'Which employees are scheduled but have low PTO accruals?' and get accurate answers from the index.
Set up UKG Pro Workforce Management MCP in LlamaIndex
Prerequisites
- Python 3.10+ installed
-
llama-index-tools-mcppackage - Active Vinkius subscription with a valid endpoint token
- 1
Install dependencies
Run
pip install llama-index-tools-mcp llama-index-llms-openai. The MCP tools package providesBasicMCPClientandMcpToolSpec. - 2
Connect with BasicMCPClient
Point
BasicMCPClientto your Vinkius endpoint URL. Replace[YOUR_TOKEN_HERE]with your token from cloud.vinkius.com. Supports SSE and Streamable HTTP transports. - 3
Convert to LlamaIndex tools
Call
mcp_tool_spec.to_tool_list_async()to convert all UKG Pro Workforce Management MCP tools into nativeFunctionToolobjects that any LlamaIndex agent can use. - 4
Run with any LLM
Create a
FunctionAgentwith the tools and your preferred LLM. SwapOpenAIforAnthropic,Gemini, or any LlamaIndex-supported provider.
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI
# Connect to the MCP
mcp_client = BasicMCPClient(
"https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)
mcp_tool_spec = McpToolSpec(client=mcp_client)
# Convert MCP tools to LlamaIndex tools
tools = await mcp_tool_spec.to_tool_list_async()
# Create and run the agent
agent = FunctionAgent(
tools=tools,
llm=OpenAI(model="gpt-4o"),
system_prompt="You have access to UKG Pro Workforce Management tools.",
)
response = await agent.run("List recent UKG Pro Workforce Management data") 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 LlamaIndex
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