How to Use the Cleared (ClearedIn) MCP in LlamaIndex

Q: How do I index Cleared (ClearedIn) background checks in LlamaIndex?

You use the listbackgroundscreenings tool to pull raw screening data. LlamaIndex converts these text payloads into document nodes, which are then embedded and stored in your vector database.

Q: How does Cleared (ClearedIn) prevent hallucinations in LlamaIndex?

Your agent queries actual data via getsignaturedetails and indexes the exact output. This grounds the agent's responses in factual API responses rather than relying on pre-trained model weights.

Q: Can I filter which Cleared tools are exposed to my indexer?

Yes, you configure the allowedtools filter during client setup. This lets you restrict the agent to only access listidentityverifications while hiding sensitive audit logs.

Pull your Cleared (ClearedIn) identity and screening logs straight into LlamaIndex vector stores using this MCP Server.

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Connect Cleared (ClearedIn) MCP to LlamaIndex

Create your Vinkius account to connect Cleared (ClearedIn) 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 Cleared (ClearedIn) with LlamaIndex

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Index Cleared security logs for semantic search

The `list_cleared_audit_logs` tool fetches historical security events to build a searchable local index. LlamaIndex ingests these raw logs, converting security events into vector embeddings. When you query your agent about past account activity, it searches this index instead of making repeated API calls. This avoids rate limits and gives you instant answers grounded in actual audit history.

Query screening details with RAG pipelines

We call `get_screening_details` to retrieve detailed background check reports and feed them into your index. Your agent uses this data to answer complex questions about applicant history. By combining live data with historical documents, your RAG pipeline gets a complete view of candidate status. You query the system in plain English to find out why a specific background check failed.

Build an identity knowledge base with this MCP Server

The `list_identity_verifications` tool retrieves all active verification records to update your local document store. LlamaIndex parses these records into nodes, making them instantly queryable. If an agent needs to verify a user's current status, it checks the local index first. For real-time confirmation, the agent falls back to calling `get_verification_details` directly through the server.

Setup guide

Set up Cleared (ClearedIn) 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 Cleared (ClearedIn) 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 Cleared (ClearedIn) tools.",
)
response = await agent.run("List recent Cleared (ClearedIn) 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 Cleared (ClearedIn). 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 Cleared (ClearedIn) MCP in LlamaIndex

You use the `list_background_screenings` tool to pull raw screening data. LlamaIndex converts these text payloads into document nodes, which are then embedded and stored in your vector database.

Yes, by registering the MCP tools with your FunctionAgent. The agent decides when to run `get_verification_details` based on the user's natural language query.

Your agent queries actual data via `get_signature_details` and indexes the exact output. This grounds the agent's responses in factual API responses rather than relying on pre-trained model weights.

Yes, you configure the allowed_tools filter during client setup. This lets you restrict the agent to only access `list_identity_verifications` while hiding sensitive audit logs.

All background screenings retrieved via the server remain in memory during the indexing process. Vinkius isolates the execution environment, ensuring no decrypted audit logs or screening results are written to persistent disk storage on our platform.

Use it with your favorite AI tools

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