How to Use the KPA Flex MCP in LlamaIndex

Q: How do I configure the KPA Flex tools in LlamaIndex?

Install llama-index-tools-mcp and initialize a BasicMCPClient with your HTTP endpoint. Wrap it in an McpToolSpec and call totoollistasync() to pass the functions to your FunctionAgent.

Q: Can LlamaIndex search through historical KPA Flex inspection notes?

Yes. You use the searchehsreports and getinspectiondetails tools to extract the free-text notes from past audits. LlamaIndex embeds these notes so you can perform semantic searches across years of safety data.

Q: Does LlamaIndex cache the KPA Flex API responses?

It indexes the output. When you call tools like getflexsitestats, the framework stores the resulting data in your configured vector database for fast retrieval during future queries.

Q: How do I restrict which KPA Flex tools my LlamaIndex agent can use?

You can pass an allowedtools filter when configuring the tool spec. This lets you restrict a specific agent to only read listsafetytrainings while blocking access to broader employee profiles.

Index your KPA Flex safety records and inspection logs into searchable vector stores using LlamaIndex.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect KPA Flex MCP to LlamaIndex

Create your Vinkius account to connect KPA Flex 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.

GDPR Free for Subscribers

Setup KPA Flex with LlamaIndex

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Index EHS Inspections with LlamaIndex MCP Server

The `kpa-flex-mcp` tools allow your LlamaIndex pipelines to pull raw compliance data directly into your knowledge base. You run `search_ehs_reports` and `list_ehs_inspections` to extract historical safety audits. The framework then chunks and embeds these text-heavy reports into a queryable vector store. Instead of guessing why a site failed an audit, your RAG application retrieves the exact text from past violations. When a user asks about forklift safety, the system queries the index and returns answers grounded in your actual company safety data. You eliminate hallucinations by relying strictly on verified API outputs.

Embed Employee Safety Profiles

Pull worker certification records using `get_employee_ehs_profile` and load them into your semantic search engine. You combine this with `list_flex_employees` to map out the entire workforce's current compliance status. LlamaIndex treats these API responses as documents, updating your index as training statuses change. A site manager can ask the chat interface which employees are cleared to operate heavy machinery. The agent queries the embedded `list_safety_trainings` data to instantly generate a list of qualified staff. The response relies entirely on the live EHS records you just ingested.

Query Assets and Custom Forms

Connect your physical equipment logs to your knowledge graph using `list_company_assets`. LlamaIndex pulls the asset tags, maintenance histories, and location data, merging it with the specific inspection requirements fetched via `list_custom_forms`. You build a unified search tool where a mechanic types a serial number and gets the exact safety checklist required for that machine. By calling `get_form_schema`, the agent understands the exact structure of the required inspection and guides the user through the compliance steps.

Setup guide

Set up KPA Flex 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 KPA Flex 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 KPA Flex tools.",
)
response = await agent.run("List recent KPA Flex data")

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by KPA Flex. 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

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

Connect KPA Flex now

Real-time monitoring

Live

visibility into every interaction

Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

60%

lower AI costs

Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about KPA Flex MCP in LlamaIndex

Install `llama-index-tools-mcp` and initialize a `BasicMCPClient` with your HTTP endpoint. Wrap it in an `McpToolSpec` and call `to_tool_list_async()` to pass the functions to your `FunctionAgent`.

Yes. You use the `search_ehs_reports` and `get_inspection_details` tools to extract the free-text notes from past audits. LlamaIndex embeds these notes so you can perform semantic searches across years of safety data.

It indexes the output. When you call tools like `get_flex_site_stats`, the framework stores the resulting data in your configured vector database for fast retrieval during future queries.

You can pass an `allowed_tools` filter when configuring the tool spec. This lets you restrict a specific agent to only read `list_safety_trainings` while blocking access to broader employee profiles.

The server handles confidential worker health and safety profiles. The V8 Isolate Sandbox ensures your queries run in a strictly ephemeral environment. Your LlamaIndex application receives the required data without exposing the underlying API credentials to the end user.

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