Moka HR MCP Server for Pydantic AI 10 tools — connect in under 2 minutes
Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Moka HR through the Vinkius and every tool is automatically validated against Pydantic schemas — catch errors at build time, not in production.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
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 Moka HR "
"(10 tools)."
),
)
result = await agent.run(
"What tools are available in Moka HR?"
)
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 Moka HR MCP Server
Empower your AI agent to orchestrate your recruitment lifecycle with Moka HR, the premier applicant tracking system for modern high-growth companies. By connecting Moka to your agent, you transform complex candidate tracking, job management, and interview coordination into a natural conversation. Your agent can instantly list open positions, retrieve candidate profiles, monitor interview schedules, and even provide recruitment summaries without you needing to navigate the complex Moka dashboard. Whether you are a hiring manager or a recruiter, your agent acts as a real-time talent assistant, keeping your hiring pipeline organized and your recruitment process efficient.
Pydantic AI validates every Moka HR 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.
What you can do
- Job Orchestration — List all active job postings and retrieve detailed requirements for any position.
- Candidate Management — Browse recruitment pipelines and manage candidate profiles, including contact details and history.
- Interview Tracking — Monitor scheduled interviews and retrieve session details instantly.
- Application Control — Manage the relationship between candidates and specific job applications.
- Hiring Insights — Retrieve high-level summaries of recruitment activity and pipeline statistics.
The Moka HR 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 Moka HR to Pydantic AI via MCP
Follow these steps to integrate the Moka HR 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 Moka HR with type-safe schemas
Why Use Pydantic AI with the Moka HR MCP Server
Pydantic AI provides unique advantages when paired with Moka HR 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 Moka HR integration code
Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors
Dependency injection system cleanly separates your Moka HR connection logic from agent behavior for testable, maintainable code
Moka HR + Pydantic AI Use Cases
Practical scenarios where Pydantic AI combined with the Moka HR MCP Server delivers measurable value.
Type-safe data pipelines: query Moka HR with guaranteed response schemas, feeding validated data into downstream processing
API orchestration: chain multiple Moka HR tool calls with Pydantic validation at each step to ensure data integrity end-to-end
Production monitoring: build validated alert agents that query Moka HR and output structured, schema-compliant notifications
Testing and QA: use Pydantic AI's dependency injection to mock Moka HR responses and write comprehensive agent tests
Moka HR MCP Tools for Pydantic AI (10)
These 10 tools become available when you connect Moka HR to Pydantic AI via MCP:
create_candidate
Add new candidate
get_application
Get application details
get_candidate
Get candidate details
get_hiring_summary
Get recruitment summary
get_interview
Get interview details
get_job
Get job details
list_applications
List job applications
list_candidates
List candidates
list_interviews
List scheduled interviews
list_jobs
List open job positions
Example Prompts for Moka HR in Pydantic AI
Ready-to-use prompts you can give your Pydantic AI agent to start working with Moka HR immediately.
"List all open job positions in our organization."
"Show me the recruitment pipeline for candidate 'Mario'."
"Get a summary of our hiring activity for this month."
Troubleshooting Moka HR MCP Server with Pydantic AI
Common issues when connecting Moka HR to Pydantic AI through the Vinkius, and how to resolve them.
MCPServerHTTP not found
pip install --upgrade pydantic-aiMoka HR + Pydantic AI FAQ
Common questions about integrating Moka HR 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.Does Pydantic AI validate MCP tool responses?
Can I switch LLM providers without changing MCP code?
Connect Moka HR with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect Moka HR to Pydantic AI
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.