How do I get Humaans API credentials?

You can generate an Access Token in your Humaans user profile settings under 'API'. Ensure you have the necessary permissions to access organizational data.

Can I see salary information?

Access to sensitive fields like salary depends on the permissions of the Access Token provided. This MCP uses the standard people and organization endpoints.

Does it support leave management?

Yes, the list_leaves tool allows you to track and monitor employee leave requests.

Humaans MCP Server for Pydantic AI 10 tools — connect in under 2 minutes

Name: Humaans
Availability: InStock
Author: Vinkius

ai.pydantic.dev/mcp

Built by Vinkius GDPR 10 Tools SDK

Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Humaans through the 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 Humaans "
            "(10 tools)."
        ),
    )

    result = await agent.run(
        "What tools are available in Humaans?"
    )
    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 Humaans MCP Server

Connect your AI agents to Humaans, the modern HRIS for global teams. This MCP server allows you to list and manage employees, track leave requests, view public holidays, and access organization data like teams, departments, and offices directly through the Humaans API. Ideal for automating HR operations and employee directory lookups.

Pydantic AI validates every Humaans tool response against typed schemas, catching data inconsistencies at build time. Connect 10 tools through the 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.

The Humaans MCP Server exposes 10 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 Humaans to Pydantic AI via MCP

Follow these steps to integrate the Humaans 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 10 tools from Humaans with type-safe schemas

Why Use Pydantic AI with the Humaans MCP Server

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

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

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

Humaans + Pydantic AI Use Cases

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

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

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

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

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

Humaans MCP Tools for Pydantic AI (10)

These 10 tools become available when you connect Humaans to Pydantic AI via MCP:

get_employee

Retrieves details for a specific employee

get_me

Gets current authenticated user info

list_departments

Lists organization departments

list_documents

Lists company and employee documents

list_employees

Lists all employees

list_leaves

Lists employee leave requests

list_offices

Lists organization offices

list_public_holidays

Lists public holidays

list_roles

Lists job roles

list_teams

Lists organization teams

Example Prompts for Humaans in Pydantic AI

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

"List all employees in the London office."

"Who is currently on leave?"

"Show me the organization chart (teams and departments)."

Troubleshooting Humaans MCP Server with Pydantic AI

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

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Humaans + Pydantic AI FAQ

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