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How to Use the Business Timezone & Holiday Scheduler MCP in AutoGen

Let your AutoGen agents debate and resolve timezone conflicts and holiday deadlines.

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Connect Business Timezone & Holiday Scheduler MCP to AutoGen

Create your Vinkius account to connect Business Timezone & Holiday Scheduler to AutoGen 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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Resolve scheduling debates with AutoGen agents

The `add_business_days` tool calculates target dates by skipping weekends and public holidays. In AutoGen, your coordinator agent can propose a date, and a compliance agent checks it using this tool. This prevents agents from agreeing on a deadline that falls on a holiday. The debate resolves only when the calculated business day matches the project constraints.

Coordinate global times across AutoGen groups

The `convert_timezone` tool shifts exact times between IANA timezone strings. Your agents use this MCP tool to translate meeting times before scheduling them across different regional representatives. This ensures that an agent representing a team in Tokyo and another in New York agree on the exact same UTC moment. No human intervention is needed to verify the conversion.

Connect this MCP Server to AutoGen workflows

This MCP Server registers its tools directly with AutoGen using the `mcp_server_tools` adapter. Setup is fast with `pip install "autogen-ext[mcp]"`. The adapter handles schema translation automatically so your agents can call timezone and holiday functions without custom parsers.

Setup guide

Set up Business Timezone & Holiday Scheduler MCP in AutoGen

Prerequisites

  • Python 3.10+ installed
  • autogen-ext[mcp] package
  • Active Vinkius subscription with a valid endpoint token
  1. 1

    Install AutoGen with MCP

    Run pip install "autogen-ext[mcp]" autogen-agentchat. The MCP extension includes mcp_server_tools for stateless tool access.

  2. 2

    Fetch tools from the MCP

    Call mcp_server_tools(SseServerParams(url=...)) with your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.

  3. 3

    Run your agent

    Pass the tools to AssistantAgent and call agent.run(). The agent invokes Business Timezone & Holiday Scheduler tools and returns structured results.

agent.py
from autogen_ext.tools.mcp import SseServerParams, mcp_server_tools
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

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

tools = await mcp_server_tools(server_params)

agent = AssistantAgent(
    name="Business Timezone & Holiday Scheduler_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent Business Timezone & Holiday Scheduler data")
print(result.messages[-1].content)

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Common questions about Business Timezone & Holiday Scheduler MCP in AutoGen

One AutoGen agent proposes a timeline, and another uses `add_business_days` to verify if the target dates hit weekends or holidays. They pass the updated dates back and forth until they reach a consensus. This ensures all schedules are realistic.
Yes, you configure which AutoGen agents receive the MCP tools during initialization. You can give the scheduling tools to a dedicated calendar agent while keeping your writer agents focused on content.
Install `autogen-ext[mcp]` and use the parameters to connect to the Vinkius MCP Server. Pass the resulting tool list to your AutoGen `AssistantAgent` constructor. The agent is then equipped to handle complex date calculations.
Yes, the MCP Server uses the standard IANA database to account for daylight saving transitions. The calculation is based on the specific date and time provided, ensuring exact offsets.
Yes, Vinkius processes your dates, times, country codes, and timezone strings inside a zero-trust V8 isolate. The sandbox is destroyed immediately after execution. Your scheduling parameters are never stored or used for model training.

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