How do I list all the holidays for a specific country in 2024?

Simply ask the agent to `list_holidays` and provide the Country code (e.g., 'US' or 'BR') and the year '2024'. It will retrieve the full list from Calendarific.

Can I filter holidays by type, like only religious holidays?

Yes! Use the `list_holidays_by_type` tool and provide the country, year, and type (e.g., 'religious'). Your agent will return only the matching observances.

How do I see which countries are supported by Calendarific?

Use the `list_supported_countries` tool. It will retrieve the complete directory of over 230 countries currently available in the Calendarific API.

Calendarific MCP Server for Pydantic AI 6 tools — connect in under 2 minutes

Name: Calendarific
Availability: InStock
Author: Vinkius

ai.pydantic.dev/mcp

Built by Vinkius GDPR 6 Tools SDK

Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Calendarific through Vinkius and every tool is automatically validated against Pydantic schemas. catch errors at build time, not in production.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

import asyncio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerHTTP

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    server = MCPServerHTTP(url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")

    agent = Agent(
        model="openai:gpt-4o",
        mcp_servers=[server],
        system_prompt=(
            "You are an assistant with access to Calendarific "
            "(6 tools)."
        ),
    )

    result = await agent.run(
        "What tools are available in Calendarific?"
    )
    print(result.data)

asyncio.run(main())

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* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About Calendarific MCP Server

Connect your Calendarific account to any AI agent and orchestrate your global scheduling, vacation planning, and local observability through natural conversation.

Pydantic AI validates every Calendarific tool response against typed schemas, catching data inconsistencies at build time. Connect 6 tools through Vinkius and switch between OpenAI, Anthropic, or Gemini without changing your integration code. full type safety, structured output guarantees, and dependency injection for testable agents.

What you can do

Holiday Oversight — List all public, religious, and local holidays for a specific country and year.
Regional Observability — Filter holidays by state or region to ensure your planning accounts for local variations.
Categorized Discovery — List holidays by type, such as National, Observance, or Religious holidays.
Country & Language Directory — Access the list of 230+ supported countries and their respective ISO codes.
Date-Specific Queries — Retrieve holidays for a specific month or day to verify work availability.
Reference Data — Get detailed metadata for each holiday, including descriptions and observance regions.

The Calendarific MCP Server exposes 6 tools through the Vinkius. Connect it to Pydantic AI in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect Calendarific to Pydantic AI via MCP

Follow these steps to integrate the Calendarific MCP Server with Pydantic AI.

Install Pydantic AI

Run pip install pydantic-ai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save to agent.py and run: python agent.py

Explore tools

The agent discovers 6 tools from Calendarific with type-safe schemas

Why Use Pydantic AI with the Calendarific MCP Server

Pydantic AI provides unique advantages when paired with Calendarific through the Model Context Protocol.

Full type safety: every MCP tool response is validated against Pydantic models, catching data inconsistencies before they reach your application

Model-agnostic architecture. switch between OpenAI, Anthropic, or Gemini without changing your Calendarific integration code

Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors

Dependency injection system cleanly separates your Calendarific connection logic from agent behavior for testable, maintainable code

Calendarific + Pydantic AI Use Cases

Practical scenarios where Pydantic AI combined with the Calendarific MCP Server delivers measurable value.

Type-safe data pipelines: query Calendarific with guaranteed response schemas, feeding validated data into downstream processing

API orchestration: chain multiple Calendarific tool calls with Pydantic validation at each step to ensure data integrity end-to-end

Production monitoring: build validated alert agents that query Calendarific and output structured, schema-compliant notifications

Testing and QA: use Pydantic AI's dependency injection to mock Calendarific responses and write comprehensive agent tests

Calendarific MCP Tools for Pydantic AI (6)

These 6 tools become available when you connect Calendarific to Pydantic AI via MCP:

get_account_info

Check the status of the integration

list_holidays

List holidays for a specific country and year

list_holidays_by_location

List holidays for a specific state or region

list_holidays_by_type

List holidays filtered by type (e.g. national, religious)

list_supported_countries

List all supported countries and their ISO codes

list_supported_languages

List all supported languages

Example Prompts for Calendarific in Pydantic AI

Ready-to-use prompts you can give your Pydantic AI agent to start working with Calendarific immediately.

"List all public holidays in Brazil for 2024."

"Are there any holidays in New York (US-NY) on December 25th?"

"Show me the religious holidays in Italy for 2024."

Troubleshooting Calendarific MCP Server with Pydantic AI

Common issues when connecting Calendarific to Pydantic AI through the Vinkius, and how to resolve them.

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Calendarific + Pydantic AI FAQ

Common questions about integrating Calendarific MCP Server with Pydantic AI.

How does Pydantic AI discover MCP tools?

Create an MCPServerHTTP instance with the server URL. Pydantic AI connects, discovers all tools, and generates typed Python interfaces automatically.

Does Pydantic AI validate MCP tool responses?

Yes. When you define result types as Pydantic models, every tool response is validated against the schema. Invalid data raises a clear error instead of silently corrupting your pipeline.

Can I switch LLM providers without changing MCP code?

Absolutely. Pydantic AI abstracts the model layer. your Calendarific MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.