Can my agent list all leave requests for the current year in Factorial?

Yes. Use the 'list_leaves' tool. You can specify the 'year' parameter, and the agent will fetch all absence and holiday requests, allowing you to track team availability flawlessly.

How do I check the shift schedule for a specific month via chat?

Use the 'list_shifts' tool. Provide the 'year' and 'month' (numeric). The agent will retrieve the detailed scheduling information, providing you with a clear view of operational coverage.

Can I audit payslip availability through the agent?

Absolutely. Use the 'list_payslips' tool for a target year and month. Your agent will verify which employees have available compensation records without you needing to manually navigate the payroll section.

Factorial MCP Server for Pydantic AI 12 tools — connect in under 2 minutes

Name: Factorial
Availability: InStock
Author: Vinkius

ai.pydantic.dev/mcp

Built by Vinkius GDPR 12 Tools SDK

Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Factorial 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 Factorial "
            "(12 tools)."
        ),
    )

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

asyncio.run(main())

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Stream every event to Splunk, Datadog, or your own webhook in real-time

* 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 Factorial MCP Server

Connect your Factorial HR account to any AI agent and take full control of your human resources management and organizational workflows through natural conversation.

Pydantic AI validates every Factorial tool response against typed schemas, catching data inconsistencies at build time. Connect 12 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

Employee & Team Orchestration — List all registered employees and teams to retrieve detailed profiles, organizational roles, and department structures natively
Leave & Absence Monitoring — Fetch all holiday and leave requests for any given year to track team availability and upcoming time-off boundaries flawlessly
Shift & Schedule Navigation — Retrieve detailed shift scheduling information for specific months to audit team rotations and operational coverage securely
Payroll Oversight — List available payslips across the organization for specific months to verify compensation records and financial trail metadata
Document Discovery — Access stored company documents and folders to retrieve HR policies and internal documentation using natural language
Company Data Auditing — Fetch global company metadata and administrative configurations to verify workspace settings and organizational identities
Personnel Intelligence — Resolve specific employee contexts including contact details, manager relationships, and hiring dates limitlessly

The Factorial MCP Server exposes 12 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 Factorial to Pydantic AI via MCP

Follow these steps to integrate the Factorial 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 12 tools from Factorial with type-safe schemas

Why Use Pydantic AI with the Factorial MCP Server

Pydantic AI provides unique advantages when paired with Factorial 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 Factorial integration code

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

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

Factorial + Pydantic AI Use Cases

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

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

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

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

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

Factorial MCP Tools for Pydantic AI (12)

These 12 tools become available when you connect Factorial to Pydantic AI via MCP:

clock_in

Clock in for a shift

clock_out

Clock out from a shift

get_employee

Get a specific Factorial employee by ID

get_me

Get current company identity info

list_documents

List all company documents

list_employees

List all Factorial employees

list_folders

List all company folders

list_holidays

List all holidays for a given year

list_leaves

List all leaves for a given year

list_payslips

List all payslips for a given year and month

list_shifts

List all shifts for a given year and month

list_teams

List all Factorial teams

Example Prompts for Factorial in Pydantic AI

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

"List all employees in the 'Engineering' team"

"Show me upcoming leave requests for June 2026"

"Find HR policy documents in the company folders"

Troubleshooting Factorial MCP Server with Pydantic AI

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

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Factorial + Pydantic AI FAQ

Common questions about integrating Factorial 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 Factorial MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.