How to Use the UKG Pro Learning MCP in CrewAI

Q: What is the best way to research UKG Pro Learning curricula using CrewAI?

You assign an agent access to the curricula tool. This allows your specialized 'Research Agent' within the crew to automatically list and compile all learning paths, providing a comprehensive report.

Q: Can I list courses for UKG Pro Learning with CrewAI?

Yes. You pass the courses tool to a specialized agent within your crew. This allows the agents to execute the necessary lookup and present the specific training data.

Run automated UKG Pro Learning research and reporting with your AI client via CrewAI.

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Connect UKG Pro Learning MCP to CrewAI

Create your Vinkius account to connect UKG Pro Learning to CrewAI 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 Learning with CrewAI

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Automate User Data Retrieval

Give a specialized agent the `users` tool. That agent can then autonomously pull employee details from UKG Pro Learning, acting like a dedicated HR research assistant. It's built for running continuous operations—letting one agent get the data and another analyze it without human babysitting.

Track All Learning Paths

You can assign an agent the `curricula` tool. This allows your 'Curriculum Agent' to constantly monitor and list all available learning paths, keeping documentation up-to-date. This setup is perfect for autonomous monitoring where a specialized team handles reporting automatically.

Process Enrollment Statuses

Use an agent with the `enrollments` tool. This allows your 'Compliance Agent' to check if specific employees are enrolled in required training, giving you continuous oversight. It executes these checks as part of a larger crew operation, ensuring nothing falls through the cracks.

Setup guide

Set up UKG Pro Learning MCP in CrewAI

Prerequisites

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

1

Install CrewAI
Run pip install crewai to install the framework. MCP support is built-in via the mcps parameter.
2

Add the MCP URL to your agent
Pass your Vinkius endpoint directly to the mcps list. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. CrewAI handles tool discovery and caching automatically.
3

Kick off your crew
Create a Crew with your agent and tasks. Call crew.kickoff() — the agent will automatically invoke UKG Pro Learning tools as needed.

crew.py

from crewai import Agent, Task, Crew

agent = Agent(
    role="UKG Pro Learning Analyst",
    goal="Access and analyze UKG Pro Learning data via MCP.",
    backstory="Expert analyst with direct UKG Pro Learning access.",
    mcps=[
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ],
)

task = Task(
    description="List recent UKG Pro Learning transactions",
    agent=agent,
    expected_output="A summary of recent activity",
)

crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)

Get your connection token →

Prerequisites

Python 3.10+ installed
crewai + crewai-tools packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install crewai crewai-tools. The MCPServerAdapter handles lifecycle management and tool conversion.
2

Connect with MCPServerAdapter
Use MCPServerAdapter as a context manager with SseServerParameters pointing to your Vinkius endpoint. The adapter automatically manages connection lifecycle.
3

Assign tools and run
Pass the returned mcp_tools to your agent's tools parameter. The adapter converts MCP tools to native BaseTool objects compatible with all CrewAI agents.

crew.py

from crewai import Agent, Task, Crew
from crewai_tools import MCPServerAdapter
from mcp import SseServerParameters

server_params = SseServerParameters(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

with MCPServerAdapter(server_params) as mcp_tools:
    agent = Agent(
        role="UKG Pro Learning Analyst",
        goal="Access and analyze UKG Pro Learning data via MCP.",
        backstory="Expert analyst with direct UKG Pro Learning access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent UKG Pro Learning transactions",
        agent=agent,
        expected_output="A summary of recent activity",
    )

    crew = Crew(agents=[agent], tasks=[task])
    result = crew.kickoff()
    print(result)

Get your connection token →

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 Learning. 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 Learning MCP in CrewAI

You assign an agent access to the `curricula` tool. This allows your specialized 'Research Agent' within the crew to automatically list and compile all learning paths, providing a comprehensive report.

You configure an agent specifically for data retrieval. That agent uses the `users` tool to pull employee information. The crew then passes that raw data to a second agent for immediate analysis.

The MCP Server handles user details, curriculum lists, and enrollment records. Your autonomous crew can check employee profiles (`users`) and their specific training paths (`enrollments`).

Yes. You pass the `courses` tool to a specialized agent within your crew. This allows the agents to execute the necessary lookup and present the specific training data.

It handles it through its multi-agent architecture. You can run a crew where one agent gets `users` data, passes it to another agent that then checks the associated `enrollments`, completing a full reporting cycle.

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