How to Use the Hurma MCP in CrewAI

Q: How do I pass Hurma tools to a CrewAI agent?

Pass your Vinkius MCP Server URL directly into the mcps array when defining your agents. This exposes tools like listemployees to the entire crew.

Q: Can I limit which Hurma tools a CrewAI agent can use?

Yes. Use MCPServerHTTP from the CrewAI package and apply a toolfilter to only expose read-only tools like getemployeedetails to junior agents.

Q: Is our Hurma payroll and overtime data safe during multi-agent runs?

We run all exportovertimes and payroll queries through an ephemeral, zero-trust sandbox. The server does not log the payload contents, shielding your sensitive HR records from external eyes.

Deploy a collaborative crew of specialized AI agents to manage your Hurma HR tasks in CrewAI with this MCP Server.

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Connect Hurma MCP to CrewAI

Create your Vinkius account to connect Hurma 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 Hurma with CrewAI

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Multi-Agent Recruitment Teams in CrewAI

The `list_candidates` tool connects your specialized CrewAI agents directly to your recruitment pipeline. This MCP integration allows an outbound recruiter agent to find new talent while a screening agent calls `get_candidate_details` to analyze experience. The agents share memory to avoid duplicating efforts. Once they agree on a candidate, a coordinator agent invokes `create_candidate` to officially log them into your system.

Autonomous Time-Off Verification

The `list_out_of_office` tool enables your operations crew to monitor team availability autonomously. A monitoring agent checks who is out and compares it against active projects. If a conflict arises, a scheduler agent uses `get_vacation_balance` to verify if alternative dates are feasible. The MCP Server handles the scheduling puzzle without manual HR intervention.

Automated Department Auditing

The `list_departments` tool lets your reporting crew map your entire organizational structure. A data analyst agent reads this structure and queries `list_employees` for each department. The crew compiles a headcount report and flags discrepancies. This runs on a schedule, giving you an accurate picture of your workforce without manual database queries.

Setup guide

Set up Hurma 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 Hurma tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

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

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

Pass your Vinkius MCP Server URL directly into the `mcps` array when defining your agents. This exposes tools like `list_employees` to the entire crew.

Yes. Use `MCPServerHTTP` from the CrewAI package and apply a `tool_filter` to only expose read-only tools like `get_employee_details` to junior agents.

Agents use shared memory to pass context. The MCP protocol enables one agent to gather data and another to use `create_leave_request` to submit the final form.

The server supports stdio, SSE, and Streamable HTTP. CrewAI easily connects over HTTP for distributed agent architectures.

We run all `export_overtimes` and payroll queries through an ephemeral, zero-trust sandbox. The server does not log the payload contents, shielding your sensitive HR records from external eyes.

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