How to Use the Certn MCP in LangChain

Q: Can LangChain agents select packages dynamically from Certn?

Yes. Your agent calls listpackages to see what checks are available, then feeds those IDs directly into invitehrapplication based on the job role.

Q: What happens if an applicant email is invalid?

The invitehrapplication tool returns an error message. Your agent catches this exception in the chain and prompts the user to correct the email address.

Run Certn background checks directly inside your LangChain chains and monitor every step with LangSmith.

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Connect Certn MCP to LangChain

Create your Vinkius account to connect Certn 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 Certn with LangChain

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Run multi-step background checks with LangChain

This MCP Server lets your agent trigger applicant invites and fetch reports as part of a single, automated run. You configure a chain that starts with `invite_hr_application` to email or text a candidate, then polls the status using `get_hr_applicant` until the check finishes. Your agent handles the logic of when to pull the final PDF. It calls `get_hr_report_pdf` when the status changes, saving the binary file directly to your storage without human intervention.

Trace screening steps using LangSmith

You connect the Certn MCP Server to your chain and get immediate observability into every API call. LangSmith traces the exact inputs sent to `quick_hr_application` and logs the raw JSON payloads returned by the service. This setup stops silent failures. If `list_packages` returns a configuration error, you see the exact token usage and latency metrics in your tracing dashboard to debug the failure in seconds.

Build conditional HR pipelines in LangChain

You write logic that changes its path based on real-time screening results. Your agent uses this MCP toolset to call `list_hr_applicants` to find pending checks, then decides whether to add extra screening steps using `add_hr_packages`. The output of one tool feeds directly into the next. When a background check completes, your agent grabs the temporary web link via `get_hr_report_link` and passes it to your internal Slack notification step.

Setup guide

Set up Certn 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 Certn 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({
    "certn-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 Certn 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 Certn. 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 Certn MCP in LangChain

You build a LangGraph state machine that polls the API. The agent calls `get_hr_applicant` at set intervals, updating the graph state until the status marks the report as ready.

Yes. Your agent calls `list_packages` to see what checks are available, then feeds those IDs directly into `invite_hr_application` based on the job role.

You write a chain that pulls candidate data from your database tool, formats it, and passes it to `quick_hr_application` for instant screening.

The `invite_hr_application` tool returns an error message. Your agent catches this exception in the chain and prompts the user to correct the email address.

Vinkius runs the server in an isolated sandbox where all traffic is encrypted. Your candidate SSNs and background PDFs never persist on the platform, passing directly from the API to your local storage.

Use it with your favorite AI tools

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