How to Use the Nager.Date MCP in AutoGen

Q: How do I enable Nager.Date tools for AutoGen agents?

Use the mcpservertools function to register the server. Then, pass the resulting tool list into your AssistantAgent constructor to give the agents access.

Q: Can AutoGen agents use Nager.Date to reach a consensus?

They can. By debating the results of getpublicholidays, agents can agree on a shared schedule that respects both local laws and global project needs.

Build consensus-driven holiday planning systems in AutoGen where agents debate regional schedule impacts.

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Create your Vinkius account to connect Nager.Date 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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Setup Nager.Date with AutoGen

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Debate holiday impacts with multi-agent teams

Assign `get_next_holidays` to an analyst agent and let it debate the results with a project manager agent. They negotiate how a public holiday affects your delivery deadlines. This setup forces agents to challenge each other. The manager checks if the holiday overlaps with a shipment, ensuring the final decision accounts for real-world constraints.

Automate cross-regional calendar checks

Use `get_next_holidays_worldwide` to gather data for a global operations agent. It synthesizes holiday info from multiple countries to flag potential bottlenecks in your supply chain. Your agents work in parallel. While one agent gathers data, the other evaluates the impact, leading to faster decisions than manual calendar review.

Negotiate based on verified API facts

The McpToolAdapter converts Nager.Date responses into a format your agents understand. When they discuss a date, they use the `is_holiday_today` tool to verify the facts. Agents don't rely on guesswork. They call the tool, receive the truth, and then reach a consensus that is based on the actual public holiday calendar.

Setup guide

Set up Nager.Date MCP in AutoGen

Prerequisites

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

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

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

Run your agent
Pass the tools to AssistantAgent and call agent.run(). The agent invokes Nager.Date 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="Nager.Date_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent Nager.Date data")
print(result.messages[-1].content)

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Prerequisites

Python 3.10+ installed
autogen-ext[mcp] + autogen-agentchat
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Same packages as above. McpWorkbench is ideal when your agent needs stateful sessions across multiple tool calls.
2

Use McpWorkbench as context manager
Wrap your agent in async with McpWorkbench(...) to maintain shared state and resources. The workbench manages the full MCP session lifecycle.
3

Run with workbench
Pass workbench=workbench to your agent. State is preserved across multiple tool calls within the same session.

agent.py

from autogen_ext.tools.mcp import McpWorkbench, SseServerParams
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"
)

async with McpWorkbench(server_params) as workbench:
    agent = AssistantAgent(
        name="Nager.Date_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent Nager.Date data")
    print(result.messages[-1].content)

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 Nager.Date. 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 Nager.Date MCP in AutoGen

Use the mcp_server_tools function to register the server. Then, pass the resulting tool list into your AssistantAgent constructor to give the agents access.

They can. By debating the results of `get_public_holidays`, agents can agree on a shared schedule that respects both local laws and global project needs.

The server handles concurrent requests from your agents. Each agent gets its own tool execution context, preventing interference during complex negotiations.

You can. The server supports stdio and HTTP transports, making it easy to run inside your automated test or deployment environments.

The server only processes public holiday dates and names. It handles no sensitive data, and all interactions are restricted to the public API endpoints.

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