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Ninehire MCP Server for LangChainGive LangChain instant access to 12 tools to Check Api Health, Get Applicant Profile, Get Authenticated User Info, and more

Built by Vinkius GDPR 12 Tools Framework

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

Ask AI about this App Connector for LangChain

The Ninehire app connector for LangChain is a standout in the Industry Titans 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

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({
        "ninehire": {
            "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 Ninehire, show me what tools are available.",
            }]
        })
        print(response["messages"][-1].content)

asyncio.run(main())
Ninehire
Fully ManagedVinkius Servers
60%Token savings
High SecurityEnterprise-grade
IAMAccess control
EU AI ActCompliant
DLPData protection
V8 IsolateSandboxed
Ed25519Audit chain
<40msKill switch
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 Ninehire MCP Server

Connect your Ninehire account to any AI agent and take full control of your talent acquisition and applicant tracking orchestration through natural conversation. Ninehire (나인하이어) provides a modern recruitment platform, and this integration allows you to retrieve job metadata, manage candidate profiles, and monitor interview evaluations directly from your chat interface.

LangChain's ecosystem of 500+ components combines seamlessly with Ninehire through native MCP adapters. Connect 12 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.

What you can do

  • Job & Requirement Orchestration — List all active job openings and retrieve detailed requirements programmatically to ensure your hiring roadmap is always synchronized.
  • Applicant & Pipeline Intelligence — Access and monitor candidate profiles and retrieve detailed application history directly from the AI interface to maintain high-fidelity talent pools.
  • Evaluation & Feedback Control — List interview scores and comments via natural language to drive better hiring decisions and team alignment.
  • Manual Applicant Ingestion — Register new applicants and manage department or location metadata using simple AI commands.
  • Operational Monitoring — Track system responses and manage recruitment webhooks to ensure your hiring workflows are always optimized.

The Ninehire MCP Server exposes 12 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.

All 12 Ninehire tools available for LangChain

When LangChain connects to Ninehire through Vinkius, your AI agent gets direct access to every tool listed below — spanning applicant-tracking, talent-acquisition, hiring-pipeline, 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.

check_api_health

Verify Ninehire API status

get_applicant_profile

Get details for a specific candidate

get_authenticated_user_info

Get current account profile

get_job_details

Get details for a specific job

list_candidate_evaluations

Get evaluations for a candidate

list_configured_webhooks

List active webhooks

list_hiring_teams

List internal hiring teams

list_job_applicants

List candidates and applicants

list_job_locations

List hiring locations

list_job_postings

Supports filtering by title, job group, and employment type. List all job openings

list_organization_departments

List company departments

register_new_applicant

Requires essential info like name and email. Add a candidate manually

Connect Ninehire to LangChain via MCP

Follow these steps to wire Ninehire into LangChain. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.

01

Install dependencies

Run pip install langchain langchain-mcp-adapters langgraph langchain-openai
02

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token
03

Run the agent

Save the code and run python agent.py
04

Explore tools

The agent discovers 12 tools from Ninehire via MCP

Why Use LangChain with the Ninehire MCP Server

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

01

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

02

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

03

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

04

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

Ninehire + LangChain Use Cases

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

01

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

02

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

03

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

04

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

Example Prompts for Ninehire in LangChain

Ready-to-use prompts you can give your LangChain agent to start working with Ninehire immediately.

01

"List all active job postings in Ninehire."

02

"Show me all candidates who applied for the Senior Developer position."

03

"List all departments and hiring locations configured in my organization."

Troubleshooting Ninehire MCP Server with LangChain

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

01

MultiServerMCPClient not found

Install: pip install langchain-mcp-adapters

Ninehire + LangChain FAQ

Common questions about integrating Ninehire MCP Server with LangChain.

01

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.
02

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.
03

Can I trace MCP tool calls in LangSmith?

Yes. All MCP tool invocations appear as traced steps in LangSmith, showing input parameters, response payloads, latency, and token usage.