Normality Test Engine MCP Server for OpenAI Agents SDKGive OpenAI Agents SDK instant access to 1 tools to Test Normality
The OpenAI Agents SDK enables production-grade agent workflows in Python. Connect Normality Test Engine through Vinkius and your agents gain typed, auto-discovered tools with built-in guardrails. no manual schema definitions required.
Ask AI about this MCP Server for OpenAI Agents SDK
The Normality Test Engine MCP Server for OpenAI Agents SDK is a standout in the Developer Tools category — giving your AI agent 1 tools to work with, ready to go from day one.
Vinkius delivers Streamable HTTP and SSE to any MCP client
import asyncio
from agents import Agent, Runner
from agents.mcp import MCPServerStreamableHttp
async def main():
# Your Vinkius token. get it at cloud.vinkius.com
async with MCPServerStreamableHttp(
url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
) as mcp_server:
agent = Agent(
name="Normality Test Engine Assistant",
instructions=(
"You help users interact with Normality Test Engine. "
"You have access to 1 tools."
),
mcp_servers=[mcp_server],
)
result = await Runner.run(
agent, "List all available tools from Normality Test Engine"
)
print(result.final_output)
asyncio.run(main())
* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
About Normality Test Engine MCP Server
Before running t-tests, ANOVA, or linear regression, you need to verify that your data is normally distributed. LLMs cannot eyeball a distribution from raw numbers — they will guess and often guess wrong.
The OpenAI Agents SDK auto-discovers all 1 tools from Normality Test Engine through native MCP integration. Build agents with built-in guardrails, tracing, and handoff patterns. chain multiple agents where one queries Normality Test Engine, another analyzes results, and a third generates reports, all orchestrated through Vinkius.
This MCP uses simple-statistics to compute exact Skewness and Kurtosis coefficients, then applies a Jarque-Bera test to determine normality. The AI gets a definitive pass/fail verdict with the exact test statistic and p-value.
The Superpowers
- Zero Hallucination: Exact statistical coefficients computed locally.
- Automated Verdict: Returns a clear 'normal' or 'not normal' interpretation.
- Descriptive Statistics: Also provides exact Mean, Std Dev, Skewness, and Kurtosis.
- Data Privacy: Your research data stays entirely on your local machine.
The Normality Test Engine MCP Server exposes 1 tools through the Vinkius. Connect it to OpenAI Agents SDK in under two minutes — credentials fully managed, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
All 1 Normality Test Engine tools available for OpenAI Agents SDK
When OpenAI Agents SDK connects to Normality Test Engine through Vinkius, your AI agent gets direct access to every tool listed below — spanning statistics, data-science, normality-test, and more. Every call runs in a secure, isolated environment with full audit visibility. Beyond a simple connection, you get real-time monitoring of agent activity, enterprise governance, and optimized token usage.
Test normality on Normality Test Engine
Perform an exact deterministic Jarque-Bera normality test on numeric data without LLM math hallucinations
Connect Normality Test Engine to OpenAI Agents SDK via MCP
Follow these steps to wire Normality Test Engine into OpenAI Agents SDK. The entire setup takes under two minutes — your credentials stay safe behind Vinkius.
Install the SDK
pip install openai-agents in your Python environmentReplace the token
[YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.comRun the script
python agent.pyExplore tools
Why Use OpenAI Agents SDK with the Normality Test Engine MCP Server
OpenAI Agents SDK provides unique advantages when paired with Normality Test Engine through the Model Context Protocol.
Native MCP integration via `MCPServerSse`, pass the URL and the SDK auto-discovers all tools with full type safety
Built-in guardrails, tracing, and handoff patterns let you build production-grade agents without reinventing safety infrastructure
Lightweight and composable: chain multiple agents and MCP servers in a single pipeline with minimal boilerplate
First-party OpenAI support ensures optimal compatibility with GPT models for tool calling and structured output
Normality Test Engine + OpenAI Agents SDK Use Cases
Practical scenarios where OpenAI Agents SDK combined with the Normality Test Engine MCP Server delivers measurable value.
Automated workflows: build agents that query Normality Test Engine, process the data, and trigger follow-up actions autonomously
Multi-agent orchestration: create specialist agents. one queries Normality Test Engine, another analyzes results, a third generates reports
Data enrichment pipelines: stream data through Normality Test Engine tools and transform it with OpenAI models in a single async loop
Customer support bots: agents query Normality Test Engine to resolve tickets, look up records, and update statuses without human intervention
Example Prompts for Normality Test Engine in OpenAI Agents SDK
Ready-to-use prompts you can give your OpenAI Agents SDK agent to start working with Normality Test Engine immediately.
"Check if this residuals array is normally distributed before I run my regression."
"Is this sensor data normally distributed or should I use a non-parametric test?"
"Run a normality test on the 'Revenue' column before I calculate confidence intervals."
Troubleshooting Normality Test Engine MCP Server with OpenAI Agents SDK
Common issues when connecting Normality Test Engine to OpenAI Agents SDK through Vinkius, and how to resolve them.
MCPServerStreamableHttp not found
pip install --upgrade openai-agentsAgent not calling tools
Normality Test Engine + OpenAI Agents SDK FAQ
Common questions about integrating Normality Test Engine MCP Server with OpenAI Agents SDK.
How does the OpenAI Agents SDK connect to MCP?
MCPServerSse(url=...) to create a server connection. The SDK auto-discovers all tools and makes them available to your agent with full type information.Can I use multiple MCP servers in one agent?
MCPServerSse instances to the agent constructor. The agent can use tools from all connected servers within a single run.Does the SDK support streaming responses?
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