How do I find my ApplicantStack API Token?

Log in to ApplicantStack, go to **Settings**, then **Edit Settings**. Your API token will be listed under the API section.

What is the subdomain?

The subdomain is the first part of your ApplicantStack URL (e.g., if your URL is `mycompany.applicantstack.com`, your subdomain is `mycompany`).

Can I move a candidate to a new stage?

Yes, use the `update_candidate` tool and provide the new stage name in the `stage` field to advance them in your workflow.

ApplicantStack MCP Server for Pydantic AI 7 tools — connect in under 2 minutes

Name: ApplicantStack
Availability: InStock
Author: Vinkius

ai.pydantic.dev/mcp

Built by Vinkius GDPR 7 Tools SDK

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

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

The ApplicantStack MCP Server integrates your recruiting and onboarding workflows directly into your AI workspace. Efficiently manage your job listings, track candidate progress through custom stages, and streamline your hiring process using simple natural language.

Pydantic AI validates every ApplicantStack tool response against typed schemas, catching data inconsistencies at build time. Connect 7 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.

Key Features

Job Management — List all active and closed job openings, and retrieve full metadata for any specific listing.
Candidate Tracking — Access your entire applicant database and filter by workflow stage or score.
Workflow Automation — Move candidates between stages (e.g., from 'Interview' to 'Hired') and update their profiles instantly.
Onboarding & Hires — Access onboarding data for new hires to ensure a smooth transition from applicant to employee.
Secure Access — Uses private access tokens to safely interact with your organization's recruiting data.

Benefits for Teams

Recruiters — Quickly check the status of candidates for multiple jobs without switching between tabs.
Hiring Managers — Review candidate profiles and scores using AI-assisted summaries.
HR Teams — Track hiring trends and ensure onboarding tasks are initiated for all new hires.

The ApplicantStack MCP Server exposes 7 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 ApplicantStack to Pydantic AI via MCP

Follow these steps to integrate the ApplicantStack 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 7 tools from ApplicantStack with type-safe schemas

Why Use Pydantic AI with the ApplicantStack MCP Server

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

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

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

ApplicantStack + Pydantic AI Use Cases

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

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

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

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

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

ApplicantStack MCP Tools for Pydantic AI (7)

These 7 tools become available when you connect ApplicantStack to Pydantic AI via MCP:

get_account_check

Verify ApplicantStack account connection

get_candidate

Get details for a specific candidate

get_job

Get details for a specific job

list_candidates

List all candidates

list_hires

List all hires (onboarding)

list_jobs

List all job listings in ApplicantStack

update_candidate

Use stage field to move them in the workflow. Update candidate information or stage

Example Prompts for ApplicantStack in Pydantic AI

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

"List all active job openings in ApplicantStack."

"Show me candidates currently in the 'Interview' stage."

"Move candidate 'C12345' to the 'Hired' stage."

Troubleshooting ApplicantStack MCP Server with Pydantic AI

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

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

ApplicantStack + Pydantic AI FAQ

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