How to Use the Certn MCP in LlamaIndex

Q: How do I index Certn screening reports in LlamaIndex?

You run gethrreportweb to pull the HTML version of the report, convert it to a document object, and insert it into your index.

Q: Can LlamaIndex query historical background check records from Certn?

Yes. Your agent calls listhrapplicants to fetch all historical records, indexes the metadata, and lets you run semantic searches over past applicant statuses.

Q: How do I map property listings to Certn applicants in LlamaIndex?

The agent queries listpmproperties and listpmapplicants to build a relational index, letting you query applicant files linked to specific rental addresses.

Q: How do I get the latest status of an application?

Call gethrapplicant using the applicant ID. The tool returns the real-time progress of the screening, which you can use to update your local document index.

Index Certn screening reports into LlamaIndex to query background check data with zero hallucinations.

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Connect Certn MCP to LlamaIndex

Create your Vinkius account to connect Certn to LlamaIndex 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 LlamaIndex

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Index live screening data into your vector store

This MCP Server converts raw background check outputs into queryable document nodes. Your agent calls `list_hr_applicants` or `list_pm_applicants` and writes the structured results directly into your vector database. You search past screenings using semantic queries instead of writing database joins. The agent reads the text content from `get_hr_report_web` and indexes it so you can query candidate histories with natural language.

Build a RAG pipeline with the Certn MCP Server

You combine live property listings with tenant applications in a single queryable index. Querying `list_listings` and `list_pm_properties` pulls current rental data, matching it against applicant profiles. When a new tenant applies, your LlamaIndex workflow triggers `quick_pm_application` to check their record. The resulting data updates your vector store, giving you an instant, grounded analysis of tenant risk.

Query background check packages with natural language

Your agent uses the MCP tool `list_packages` to fetch your active screening configurations and index them. When you ask which package fits a new hire, the agent matches your query against the indexed package descriptions. This eliminates manual lookups. The agent identifies the correct package ID from the index and immediately feeds it to `invite_hr_application` to start the candidate screening.

Setup guide

Set up Certn MCP in LlamaIndex

Prerequisites

Python 3.10+ installed
llama-index-tools-mcp package
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai. The MCP tools package provides BasicMCPClient and McpToolSpec.
2

Connect with BasicMCPClient
Point BasicMCPClient to your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports SSE and Streamable HTTP transports.
3

Convert to LlamaIndex tools
Call mcp_tool_spec.to_tool_list_async() to convert all Certn MCP tools into native FunctionTool objects that any LlamaIndex agent can use.
4

Run with any LLM
Create a FunctionAgent with the tools and your preferred LLM. Swap OpenAI for Anthropic, Gemini, or any LlamaIndex-supported provider.

agent.py

from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI

# Connect to the MCP
mcp_client = BasicMCPClient(
    "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)
mcp_tool_spec = McpToolSpec(client=mcp_client)

# Convert MCP tools to LlamaIndex tools
tools = await mcp_tool_spec.to_tool_list_async()

# Create and run the agent
agent = FunctionAgent(
    tools=tools,
    llm=OpenAI(model="gpt-4o"),
    system_prompt="You have access to Certn tools.",
)
response = await agent.run("List recent Certn data")

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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 LlamaIndex

You run `get_hr_report_web` to pull the HTML version of the report, convert it to a document object, and insert it into your index.

Yes. Your agent calls `list_hr_applicants` to fetch all historical records, indexes the metadata, and lets you run semantic searches over past applicant statuses.

The agent queries `list_pm_properties` and `list_pm_applicants` to build a relational index, letting you query applicant files linked to specific rental addresses.

Call `get_hr_applicant` using the applicant ID. The tool returns the real-time progress of the screening, which you can use to update your local document index.

All data passing through the MCP Server is processed in memory inside a zero-trust V8 sandbox. Your tenant application details and screening HTML are never stored on Vinkius servers, ensuring complete data privacy.

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