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 LangChain 7 tools — connect in under 2 minutes

Name: ApplicantStack
Availability: InStock
Author: Vinkius

python.langchain.com/docs/integrations/tools/mcp

Built by Vinkius GDPR 7 Tools Framework

LangChain is the leading Python framework for composable LLM applications. Connect ApplicantStack through Vinkius and LangChain agents can call every tool natively. combine them with retrievers, memory, and output parsers for sophisticated AI pipelines.

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 langchain_mcp_adapters.client import MultiServerMCPClient
from langchain_openai import ChatOpenAI
from langgraph.prebuilt import create_react_agent

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    async with MultiServerMCPClient({
        "applicantstack": {
            "transport": "streamable_http",
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
        }
    }) as client:
        tools = client.get_tools()
        agent = create_react_agent(
            ChatOpenAI(model="gpt-4o"),
            tools,
        )
        response = await agent.ainvoke({
            "messages": [{
                "role": "user",
                "content": "Using ApplicantStack, show me what tools are available.",
            }]
        })
        print(response["messages"][-1].content)

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.

LangChain's ecosystem of 500+ components combines seamlessly with ApplicantStack through native MCP adapters. Connect 7 tools via Vinkius and use ReAct agents, Plan-and-Execute strategies, or custom agent architectures. with LangSmith tracing giving full visibility into every tool call, latency, and token cost.

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 LangChain 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 LangChain via MCP

Follow these steps to integrate the ApplicantStack MCP Server with LangChain.

Install dependencies

Run pip install langchain langchain-mcp-adapters langgraph langchain-openai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save the code and run python agent.py

Explore tools

The agent discovers 7 tools from ApplicantStack via MCP

Why Use LangChain with the ApplicantStack MCP Server

LangChain provides unique advantages when paired with ApplicantStack through the Model Context Protocol.

The largest ecosystem of integrations, chains, and agents. combine ApplicantStack MCP tools with 500+ LangChain components

Agent architecture supports ReAct, Plan-and-Execute, and custom strategies with full MCP tool access at every step

LangSmith tracing gives you complete visibility into tool calls, latencies, and token usage for production debugging

Memory and conversation persistence let agents maintain context across ApplicantStack queries for multi-turn workflows

ApplicantStack + LangChain Use Cases

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

RAG with live data: combine ApplicantStack tool results with vector store retrievals for answers grounded in both real-time and historical data

Autonomous research agents: LangChain agents query ApplicantStack, synthesize findings, and generate comprehensive research reports

Multi-tool orchestration: chain ApplicantStack tools with web scrapers, databases, and calculators in a single agent run

Production monitoring: use LangSmith to trace every ApplicantStack tool call, measure latency, and optimize your agent's performance

ApplicantStack MCP Tools for LangChain (7)

These 7 tools become available when you connect ApplicantStack to LangChain 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 LangChain

Ready-to-use prompts you can give your LangChain 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 LangChain

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

MultiServerMCPClient not found

Install: pip install langchain-mcp-adapters

ApplicantStack + LangChain FAQ

Common questions about integrating ApplicantStack MCP Server with LangChain.

How does LangChain connect to MCP servers?

Use langchain-mcp-adapters to create an MCP client. LangChain discovers all tools and wraps them as native LangChain tools compatible with any agent type.

Which LangChain agent types work with MCP?

All agent types including ReAct, OpenAI Functions, and custom agents work with MCP tools. The tools appear as standard LangChain tools after the adapter wraps them.