How to Use the Chi-Square Test Engine MCP in LlamaIndex

Index your statistical findings. LlamaIndex and Chi-Square Test Engine turn raw p-values into searchable knowledge.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect Chi-Square Test Engine MCP to LlamaIndex

Create your Vinkius account to connect Chi-Square Test Engine 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 Chi-Square Test Engine with LlamaIndex

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Statistical RAG for LlamaIndex

Perform precise calculations and immediately push the results into your vector store. The `calculate_chi_square` tool provides the hard data that your LlamaIndex agent then indexes for future retrieval. You no longer rely on vague summaries of past tests. Your knowledge base contains the actual, exact statistics generated by the engine during previous sessions.

Ground your index in exact data

Call `calculate_chi_square` to generate definitive insights from your categorical data. LlamaIndex takes this output and grounds your agent's future responses in verified math. This prevents your RAG application from drifting into speculative territory. The answers you get back are tied directly to the test results you performed earlier.

Automated analytical indexing

Set up your agent to run tests on new datasets as they arrive. The MCP tool processes the contingency table, and the result is ingested into your index automatically. Your search queries now return factual test results instead of generated guesses. It turns your documentation into a living record of your statistical work.

Setup guide

Set up Chi-Square Test Engine 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 Chi-Square Test Engine 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 Chi-Square Test Engine tools.",
)
response = await agent.run("List recent Chi-Square Test Engine 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 jstat. 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 Chi-Square Test Engine 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 Chi-Square Test Engine MCP in LlamaIndex

Install llama-index-tools-mcp and configure a BasicMCPClient. Convert the tools using McpToolSpec and pass them to your FunctionAgent to begin querying.

The server provides the data, and LlamaIndex handles the indexing. You can store the output of the tool as metadata or as part of a document node.

It keeps your environment clean while providing a standardized interface. LlamaIndex agents can discover and call these tools dynamically as needed.

The server operates in a secure, ephemeral sandbox. It processes your contingency tables in memory and does not share or store your data anywhere.

Your data is treated as transient input. Since the server is stateless, the inputs used for your Chi-Square tests are purged as soon as the result is returned.

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