Bring Statistics
to Mastra AI
Learn how to connect Normality Test Engine to Mastra AI and start using 1 AI agent tools in minutes. Fully managed, enterprise secure, and ready to use without writing a single line of code.
GDPR Free for SubscribersCompatible with every major AI agent and IDE
Gemini
What is the 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.
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.
Built-in capabilities (1)
Perform an exact deterministic Jarque-Bera normality test on numeric data without LLM math hallucinations
Why Mastra AI?
Mastra's agent abstraction provides a clean separation between LLM logic and Normality Test Engine tool infrastructure. Connect 1 tools through Vinkius and use Mastra's built-in workflow engine to chain tool calls with conditional logic, retries, and parallel execution. deployable to any Node.js host in one command.
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Mastra's agent abstraction provides a clean separation between LLM logic and tool infrastructure. add Normality Test Engine without touching business code
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Built-in workflow engine chains MCP tool calls with conditional logic, retries, and parallel execution for complex automation
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TypeScript-native: full type inference for every Normality Test Engine tool response with IDE autocomplete and compile-time checks
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One-command deployment to any Node.js host. Vercel, Railway, Fly.io, or your own infrastructure
Normality Test Engine in Mastra AI
Normality Test Engine and 4,000+ other MCP servers. One platform. One governance layer.
Teams that connect Normality Test Engine to Mastra AI through Vinkius don't need to source, host, or maintain individual MCP servers. Every tool call runs inside a hardened runtime with credential isolation, DLP, and a signed audit chain.
Raw MCP | Vinkius | |
|---|---|---|
| Server catalog | Find and host yourself | 4,000+ managed |
| Infrastructure | Self-hosted | Sandboxed V8 isolates |
| Credential handling | Plaintext in config | Vault + runtime injection |
| Data loss prevention | None | Configurable DLP policies |
| Kill switch | None | Global instant shutdown |
| Financial circuit breakers | None | Per-server limits + alerts |
| Audit trail | None | Ed25519 signed logs |
| SIEM log streaming | None | Splunk, Datadog, Webhook |
| Honeytokens | None | Canary alerts on leak |
| Custom domains | Not applicable | DNS challenge verified |
| GDPR compliance | Manual effort | Automated purge + export |
Why teams choose Vinkius for Normality Test Engine in Mastra AI
The Normality Test Engine 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. All 1 tools execute in hardened sandboxes optimized for native MCP execution.
Your AI agents in Mastra AI only access the data you authorize, with DLP that blocks sensitive information from ever reaching the model, kill switch for instant shutdown, and up to 60% token savings. Enterprise-grade infrastructure, zero maintenance.
* 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
How Vinkius secures
Normality Test Engine for Mastra AI
Every tool call from Mastra AI to the Normality Test Engine MCP Server is protected by DLP redaction, cryptographic audit chains, V8 sandbox isolation, kill switch, and financial circuit breakers.
Frequently asked questions
Is this the Shapiro-Wilk test?
This engine implements the Jarque-Bera normality test, which uses Skewness and Kurtosis. It is highly effective for medium-to-large samples and avoids the Shapiro-Wilk implementation gaps in JavaScript.
How many data points do I need?
The Jarque-Bera test works best with 30 or more samples. For very small samples (n < 20), consider using visual QQ-plot analysis as a complement.
What does a 'not normal' result mean for my analysis?
If your data is not normally distributed, parametric tests like t-tests and ANOVA may be unreliable. Consider using non-parametric alternatives like Spearman correlation or Mann-Whitney U tests.
How does Mastra AI connect to MCP servers?
Create an MCPClient with the server URL and pass it to your agent. Mastra discovers all tools and makes them available with full TypeScript types.
Can Mastra agents use tools from multiple servers?
Yes. Pass multiple MCP clients to the agent constructor. Mastra merges all tool schemas and the agent can call any tool from any server.
Does Mastra support workflow orchestration?
Yes. Mastra has a built-in workflow engine that lets you chain MCP tool calls with branching logic, error handling, and parallel execution.
createMCPClient not exported
Install: npm install @mastra/mcp
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