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WebHR MCP Server for Pydantic AIGive Pydantic AI instant access to 11 tools to Get Attendance Summary, Get Employee Details, List Attendance Logs, and more

Built by Vinkius GDPR 11 Tools SDK

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

Ask AI about this App Connector for Pydantic AI

The WebHR app connector for Pydantic AI is a standout in the Industry Titans category — giving your AI agent 11 tools to work with, ready to go from day one.

Vinkius delivers Streamable HTTP and SSE to any MCP client

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 WebHR "
            "(11 tools)."
        ),
    )

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

asyncio.run(main())
WebHR
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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 WebHR MCP Server

Connect your WebHR account to any AI agent to automate your human resource management and personnel tracking. WebHR provides a comprehensive cloud-based HRMS for managing the entire employee lifecycle—from recruitment and onboarding to attendance monitoring and leave management.

Pydantic AI validates every WebHR tool response against typed schemas, catching data inconsistencies at build time. Connect 11 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 Orchestration — List and retrieve detailed metadata for all staff records, including personal profiles and department hierarchies.
  • Attendance Monitoring — Access real-time clock-in/out records and retrieve aggregated attendance summaries for your organization.
  • Leave Management — Track leave requests, monitor balance details, and list different leave types available in your system.
  • Recruitment Control — Monitor open job postings, list active candidates, and manage the recruitment pipeline programmatically.
  • Structural Oversight — Access company locations and department definitions to maintain a clear overview of your organizational structure.

The WebHR MCP Server exposes 11 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.

All 11 WebHR tools available for Pydantic AI

When Pydantic AI connects to WebHR through Vinkius, your AI agent gets direct access to every tool listed below — spanning employee-management, attendance-tracking, recruitment, and more. Every call is secured with network, filesystem, subprocess, and code evaluation entitlements inside a sandboxed runtime. Beyond a simple connection, you get a full AI Gateway with real-time visibility into agent activity, enterprise governance, and optimized token usage.

get_attendance_summary

Get aggregated attendance metrics

get_employee_details

Get details for an employee

list_attendance_logs

List clock-in/out records

list_available_leave_types

List categories of leave

list_company_departments

g. Sales, Engineering). List organizational departments

list_employees

List organization employees

list_job_candidates

List applicants for positions

list_job_postings

List open job positions

list_job_requests

List internal job requisitions

list_leave_requests

List employee leave history

list_office_locations

List company offices

Connect WebHR to Pydantic AI via MCP

Follow these steps to wire WebHR into Pydantic AI. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.

01

Install Pydantic AI

Run pip install pydantic-ai
02

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token
03

Run the agent

Save to agent.py and run: python agent.py
04

Explore tools

The agent discovers 11 tools from WebHR with type-safe schemas

Why Use Pydantic AI with the WebHR MCP Server

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

01

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

02

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

03

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

04

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

WebHR + Pydantic AI Use Cases

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

01

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

02

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

03

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

04

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

Example Prompts for WebHR in Pydantic AI

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

01

"Check the status of our open 'Senior Frontend Engineer' job posting and list all the active candidates currently in the pipeline."

02

"Retrieve all pending leave requests for the Engineering department and check the available vacation balance for 'Marcus Johnson'."

03

"Generate an attendance summary for the New York office to see how many employees clocked in late this week."

Troubleshooting WebHR MCP Server with Pydantic AI

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

01

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

WebHR + Pydantic AI FAQ

Common questions about integrating WebHR MCP Server with Pydantic AI.

01

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.
02

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.
03

Can I switch LLM providers without changing MCP code?

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