How to Use the Ninehire MCP in LangChain

Build recruitment chains in LangChain that move candidates from application to evaluation without manual data entry.

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Connect Ninehire MCP to LangChain

Create your Vinkius account to connect Ninehire to LangChain and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup Ninehire with LangChain

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Automate candidate intake pipelines

Trigger `register_new_applicant` directly from your LangChain agents to capture candidate data the moment it arrives. You stop wasting time on manual input and let your agent handle the initial registration. Your pipeline stays clean because every call is logged through your existing infrastructure. This MCP Server ensures that incoming data flows immediately into your hiring workflow.

Chain hiring decisions with agent logic

Use `list_job_applicants` to feed raw data into your reasoning chains for automated screening. You decide the criteria, and the agent processes the list based on your specific requirements. Connect `list_candidate_evaluations` to the next step in your chain to get immediate feedback on a candidate. It forces a clear, repeatable path from application to status update.

Sync hiring operations across departments

Map your internal structure using `list_organization_departments` and `list_hiring_teams` to route candidates to the right people. Your agents use this data to ensure the right hiring manager gets the notification. Verify your system is ready with `check_api_health` before running heavy batch operations. It gives you the confidence that your agent-driven recruitment process won't hit a wall mid-execution.

Setup guide

Set up Ninehire MCP in LangChain

Prerequisites

Python 3.10+ installed
langchain-mcp-adapters + langgraph packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install langchain-mcp-adapters langgraph langchain-openai. The MCP adapters package converts MCP tools into native LangChain BaseTool objects.
2

Connect via HTTP transport
Use MultiServerMCPClient with "transport": "http" pointing to your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Create a ReAct agent
Pass the discovered tools to create_react_agent() from LangGraph. The agent automatically routes Ninehire tool calls through the MCP protocol.
4

Run with any LLM
Swap ChatOpenAI for ChatAnthropic, ChatGoogleGenerativeAI, or any LangChain-compatible model. The MCP tools work identically across all providers.

agent.py

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

async with MultiServerMCPClient({
    "ninehire-mcp": {
        "transport": "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,
    )
    result = await agent.ainvoke({
        "messages": "List recent Ninehire transactions"
    })
    print(result["messages"][-1].content)

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Ninehire. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

Why Choose Vinkius

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Common questions about Ninehire MCP in LangChain

Install the necessary adapters and initialize the server via the MCP client. Once connected, pull the tool list and inject them into your agent's execution loop.

Yes. You can use the listing tools to pull applicant data and apply your own filtering logic within the chain. The agent handles the sorting based on your prompt instructions.

Absolutely. You can aggregate this server with others to build complex workflows. LangChain handles the tool routing while the Ninehire tools manage your recruitment data.

The server returns standard responses that your agent can parse. If a request fails, you can catch the error in your chain and trigger a retry or alert.

Your candidate names and email addresses stay within your defined execution environment. We don't store your data; we just facilitate the connection between the API and your agent.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

OpenAI Agents SDK sdk-python

Google ADK sdk-python

Pydantic AI sdk-python

Vercel AI SDK sdk-typescript