Hurma MCP Server for Pydantic AIGive Pydantic AI instant access to 12 tools to Create Candidate, Create Leave Request, Export Overtimes, and more
Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Hurma 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 Hurma app connector for Pydantic AI is a standout in the Productivity category — giving your AI agent 12 tools to work with, ready to go from day one.
Vinkius delivers Streamable HTTP and SSE to any MCP client
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 Hurma "
"(12 tools)."
),
)
result = await agent.run(
"What tools are available in Hurma?"
)
print(result.data)
asyncio.run(main())
* 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 Hurma MCP Server
Connect your Hurma instance to any AI agent and manage your HR operations through natural conversation.
Pydantic AI validates every Hurma 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
- Recruiting Pipeline — List all candidates, inspect profiles, create new candidate records, and track hiring progress
- Employee Directory — Browse all employees with department and position details
- Time-Off Management — Monitor out-of-office schedules and leave requests
- Department Structure — Browse organizational departments
- Position Management — List all job positions
- Onboarding Tracking — Monitor new hire checklists and progress
The Hurma 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.
All 12 Hurma tools available for Pydantic AI
When Pydantic AI connects to Hurma through Vinkius, your AI agent gets direct access to every tool listed below — spanning employee-directory, time-off-tracking, onboarding, 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.
Create a new candidate
Create a new leave or absence request
Export overtime data
Get details for a specific candidate
Get details for a specific employee
Get employee vacation balance
List recruitment candidates
List custom field definitions
List all company departments
List all employees
List employees currently out of office
List recruitment stages
Connect Hurma to Pydantic AI via MCP
Follow these steps to wire Hurma into Pydantic AI. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.
Install Pydantic AI
pip install pydantic-aiReplace the token
[YOUR_TOKEN_HERE] with your Vinkius tokenRun the agent
agent.py and run: python agent.pyExplore tools
Why Use Pydantic AI with the Hurma MCP Server
Pydantic AI provides unique advantages when paired with Hurma 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 Hurma integration code
Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors
Dependency injection system cleanly separates your Hurma connection logic from agent behavior for testable, maintainable code
Hurma + Pydantic AI Use Cases
Practical scenarios where Pydantic AI combined with the Hurma MCP Server delivers measurable value.
Type-safe data pipelines: query Hurma with guaranteed response schemas, feeding validated data into downstream processing
API orchestration: chain multiple Hurma tool calls with Pydantic validation at each step to ensure data integrity end-to-end
Production monitoring: build validated alert agents that query Hurma and output structured, schema-compliant notifications
Testing and QA: use Pydantic AI's dependency injection to mock Hurma responses and write comprehensive agent tests
Example Prompts for Hurma in Pydantic AI
Ready-to-use prompts you can give your Pydantic AI agent to start working with Hurma immediately.
"Show all candidates in the pipeline and employees out of office this week."
"List all employees in Engineering and create a new candidate for Senior Backend."
"Show onboarding status for new hires and all departments."
Troubleshooting Hurma MCP Server with Pydantic AI
Common issues when connecting Hurma to Pydantic AI through the Vinkius, and how to resolve them.
MCPServerHTTP not found
pip install --upgrade pydantic-aiHurma + Pydantic AI FAQ
Common questions about integrating Hurma MCP Server with Pydantic AI.
How does Pydantic AI discover MCP tools?
MCPServerHTTP instance with the server URL. Pydantic AI connects, discovers all tools, and generates typed Python interfaces automatically.