How to Use the Calendarific MCP in AutoGen

Q: How do I load Calendarific tools into an AutoGen agent?

Install autogen-extmcp. Use mcpservertools with your Vinkius HTTP URL to generate the tool list. Pass that list directly into your AssistantAgent constructor.

Q: Does this MCP Server support streaming HTTP?

It does. You configure StreamableHttpServerParams in your setup script. The tool execution results stream directly into the conversation history for the agents to analyze.

Give your AutoGen multi-agent teams direct access to global holiday data via this MCP Server to negotiate international scheduling conflicts.

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Connect Calendarific MCP to AutoGen

Create your Vinkius account to connect Calendarific 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 Calendarific with AutoGen

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Perplexity

Resolve Date Conflicts in AutoGen

Scheduling across borders requires deliberation. You assign this MCP Server to a calendar agent, which pulls dates using `list_holidays`. A separate planning agent reviews those dates and argues against scheduling a release on a major public holiday. They debate the constraints until they reach consensus. If the deployment team is in Quebec, the calendar agent runs `list_holidays_by_location` to check provincial observances before finalizing the timeline.

Verify Regional and Language Support

Agents need to know their own blind spots. Before a translation agent starts localizing a marketing campaign, it asks the data agent to run `list_supported_languages` and `list_supported_countries`. The team adjusts its strategy based on the exact ISO codes returned. They do not guess which regions are covered. The conversation shifts based on hard API facts pulled mid-debate.

Filter Specific Observance Types

Your agents isolate exact data points to avoid token bloat. One agent executes `list_holidays_by_type` to find only banking holidays. It presents this filtered list to the financial agent for review. The financial agent pushes back if the dates conflict with fiscal reporting. They negotiate a new timeline. The `McpToolAdapter` handles all the schema conversions behind the scenes so the agents just talk.

Setup guide

Set up Calendarific 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 Calendarific 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="Calendarific_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

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

Get your connection token →

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="Calendarific_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent Calendarific 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 Calendarific. 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 Calendarific MCP in AutoGen

Install `autogen-ext[mcp]`. Use `mcp_server_tools` with your Vinkius HTTP URL to generate the tool list. Pass that list directly into your `AssistantAgent` constructor.

Yes. You can equip different agents in your chat with the same tools. They will call endpoints like `get_account_info` independently to verify integration status during their debate.

Autonomous systems fail when they ignore local context. Giving your agents access to exact regional holidays prevents them from agreeing on impossible deadlines during their negotiation phase.

It does. You configure `StreamableHttpServerParams` in your setup script. The tool execution results stream directly into the conversation history for the agents to analyze.

Your agents pull public country codes and generic calendar dates. Vinkius manages the authentication layer entirely off-site. The temporary execution environment terminates the moment the holiday data hits your chat thread.

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