How to Use the Days Between Dates Calculator MCP in CrewAI

Q: Can I filter which tools from the Days Between Dates Calculator my CrewAI agent sees?

Use the toolfilter option in your agent setup to restrict access. This ensures your agents only use the specific date tools you want them to have.

Coordinate specialized agents in CrewAI using accurate date math and scheduling tools.

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Works with every AI agent you already use

…and any MCP-compatible client

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Connect Days Between Dates Calculator MCP to CrewAI

Create your Vinkius account to connect Days Between Dates Calculator to CrewAI — we handle the hosting, security, and runtime updates so you don't have to. No server setup required.

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Setup Days Between Dates Calculator with CrewAI

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Coordinate date logic in CrewAI

Assign `count_business_days` to your research agent to determine project timelines. The agent uses this to inform the rest of the crew about upcoming deadlines. It turns abstract dates into concrete numbers for your autonomous team.

Detailed temporal insights

Let your analysis agent trigger `get_date_breakdown` to evaluate performance over specific periods. The data helps the crew refine their output based on the duration of past tasks. Your agents now have a clear sense of time when planning their next move.

Holiday-aware agent operations

Use `verify_holiday_status` so your CrewAI agents avoid scheduling actions on non-working days. It prevents your agents from bothering staff during holidays. This adds a layer of operational awareness to your autonomous crew.

Setup guide

Set up Days Between Dates Calculator 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 Days Between Dates Calculator tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

task = Task(
    description="List recent Days Between Dates Calculator transactions",
    agent=agent,
    expected_output="A summary of recent activity",
)

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

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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="Days Between Dates Calculator Analyst",
        goal="Access and analyze Days Between Dates Calculator data via MCP.",
        backstory="Expert analyst with direct Days Between Dates Calculator access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent Days Between Dates Calculator 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 →

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