How to Use the WebHR MCP in CrewAI

Q: Does WebHR support departmental lookups with CrewAI?

It does. You use listcompanydepartments to establish the organizational boundaries. This data feeds into other tools, allowing agents to act only within specified departments.

Run autonomous HR operations using WebHR with specialized multi-agent teams in CrewAI.

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Connect WebHR MCP to CrewAI

Create your Vinkius account to connect WebHR 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 WebHR with CrewAI

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Coordinate Job Recruitment Teams

The MCP Server lets you set up a crew of agents. Agent A can run `list_job_postings` to research open roles, while Agent B analyzes the results using `list_job_candidates`. They work together in sequence. A monitor agent watches this process, ensuring that every job posting is checked against internal requisitions via `list_job_requests` before proceeding.

Audit Team Attendance Records

You can assign a specialized 'Auditor Agent' to the crew. This agent calls `get_attendance_summary` to get metrics, and another 'Detail Agent' uses `list_attendance_logs` for granular data. The agents share memory; once they list company departments using `list_company_departments`, all subsequent actions know exactly which department is being discussed.

Manage Employee Status Checks

Need to check if someone can take time off? The crew runs specialized tasks. One agent calls `list_available_leave_types` for the categories, and another calls `list_job_candidates` to see if the person is still in good standing. This role-based specialization ensures that no critical step—like verifying department membership via `list_company_departments`—is missed.

Setup guide

Set up WebHR 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 WebHR tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

task = Task(
    description="List recent WebHR 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="WebHR Analyst",
        goal="Access and analyze WebHR data via MCP.",
        backstory="Expert analyst with direct WebHR access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent WebHR 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 WebHR. 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 WebHR MCP in CrewAI

You define specialized roles for agents, and they use the MCP Server to pull data. For example, one agent researches job openings using `list_job_postings`, while another drafts a communication based on that data.

The server provides attendance metrics, employee details via `get_employee_details`, and organizational structure. This covers everything from roles to leave history.

Yes. You can create a team where one agent lists open positions (`list_job_postings`), and another compiles the list of all internal requisitions (`list_job_requests`) to compare them.

It does. You use `list_company_departments` to establish the organizational boundaries. This data feeds into other tools, allowing agents to act only within specified departments.

This MCP Server manages structured employment records, including department information (`list_company_departments`) and full personnel profiles. This ensures your agents work with accurate, foundational data.

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