How to Use the Humaans MCP in LangChain

Build automated HR workflows in LangChain by connecting your agents directly to live Humaans employee and leave data.

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Connect Humaans MCP to LangChain

Create your Vinkius account to connect Humaans 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 Humaans with LangChain

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Claude

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Chain HR data into agent workflows

Your agent can now pull real-time personnel data directly from Humaans into your LangChain pipelines. Use `list_employees` to feed a roster into a processing chain or `get_employee` to fetch specific details for automated onboarding tasks. This MCP server turns Humaans into a readable data source for your agents. You define the logic, and the agent handles the `list_teams` or `list_departments` queries as part of its reasoning process.

Synchronize leave requests with LangChain

Automate your time-off tracking by plugging `list_leaves` into your LangGraph nodes. The agent evaluates current leave status and makes decisions based on the actual Humaans schedule. Everything happens within the chain flow. By linking `list_public_holidays` with your internal calendar logic, you stop guessing about availability and start building on verified HR data.

Manage documents and roles with LangChain

Query your company's internal structure by invoking `list_roles` or `list_documents` directly from your agentic loop. You'll get raw access to your HRIS metadata without writing custom middleware. This setup allows for complex reasoning where the agent reconciles document access with employee roles. It's built for developers who want to move past simple API calls and into true autonomous HR operations.

Setup guide

Set up Humaans 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 Humaans 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({
    "humaans-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 Humaans 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 Humaans. 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.

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Common questions about Humaans MCP in LangChain

You install the adapters and register the server as a tool source. The agent then dynamically invokes the 10 available tools based on your prompt requirements.

Yes, by utilizing the MCP standard, your agent queries the live API for every request. This ensures that `get_me` and `list_employees` always reflect the current state of your HRIS.

Vinkius handles the authentication layer for you. You only provide your endpoint token, keeping your sensitive API keys out of your local LangChain code.

LangChain allows you to aggregate this MCP server with other data sources. You can combine Humaans data with database lookups in a single agent workflow.

Your agent only accesses the specific employee records and leave balances you explicitly request. No PII is stored or cached by the server; it acts as a direct, ephemeral bridge to your Humaans account.

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