Claude CodeCLI

Feature Scaler Engine MCP Server

Bring Data Normalization
to Claude Code

Name: Feature Scaler Engine MCP Server
Price: 29 USD
Availability: InStock
Rating: 5.0 (1 reviews)
Author: Vinkius

Learn how to connect Feature Scaler Engine to Claude Code 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 Subscribers

Scale Features

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What is the Feature Scaler Engine MCP Server?

Neural Networks and K-Means clustering algorithms fail spectacularly if features aren't normalized. If an LLM attempts to subtract the mean and divide by the standard deviation across 5,000 rows, it will hallucinate 90% of the math.

This MCP brings deterministic Feature Scaling to your AI using simple-statistics. The AI specifies whether it wants Standard scaling (Mean=0, Variance=1) or MinMax scaling (Range 0-1), and the engine flawlessly transforms the target columns in milliseconds — returning the exact computed metrics for auditability.

The Superpowers

Flawless Normalization: No LLM math hallucinations — exact scaling computed by your CPU.
Multi-Column Support: Scale multiple features simultaneously in a single call.
Automated Metric Extraction: Returns the exact Means, Std Devs, Mins, and Maxs used for scaling.
Data Privacy: Your sensitive training data stays entirely on your machine.

Built-in capabilities (1)

scale_features

Deterministically Standardize (Z-Score) or MinMax Scale numeric columns offline

Why Claude Code?

Claude Code registers Feature Scaler Engine as an MCP server in a single terminal command. Once connected, Claude Code discovers all 1 tools at runtime and can call them headlessly. ideal for CI/CD pipelines, cron jobs, and automated workflows where Feature Scaler Engine data drives decisions without human intervention.

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Single-command setup: claude mcp add registers the server instantly. no config files to edit or applications to restart
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Terminal-native workflow means MCP tools integrate seamlessly into shell scripts, CI/CD pipelines, and automated DevOps tasks
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Claude Code runs headlessly, enabling unattended batch processing using Feature Scaler Engine tools in cron jobs or deployment scripts
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Built by the same team that created the MCP protocol, ensuring first-class compatibility and the fastest adoption of new protocol features

See it in action

Feature Scaler Engine in Claude Code

AI Agent→Vinkius

High Security·Kill Switch·Plug and Play

Why Vinkius

Feature Scaler Engine and 4,000+ other MCP servers. One platform. One governance layer.

Teams that connect Feature Scaler Engine to Claude Code 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.

4,000+MCP Servers ready

<40msCold start

60%Token savings

	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

Unlock for AI Agents View step-by-step setup guide for Claude Code →

Enterprise Security

Why teams choose Vinkius for Feature Scaler Engine in Claude Code

The Feature Scaler 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 Claude Code 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.

Unlock for AI Agents View full Feature Scaler Engine details →

Fully ManagedVinkius Servers

60%Token savings

High SecurityEnterprise-grade

IAMAccess control

EU AI ActCompliant

DLPData protection

V8 IsolateSandboxed

Ed25519Audit chain

<40msKill switch

Stream every event to Splunk, Datadog, or your own webhook in real-time

* 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

The Vinkius Advantage

How Vinkius secures
Feature Scaler Engine for Claude Code

Every tool call from Claude Code to the Feature Scaler Engine MCP Server is protected by DLP redaction, cryptographic audit chains, V8 sandbox isolation, kill switch, and financial circuit breakers.

< 40msCold start

Ed25519Signed audit chain

60%Token savings

FAQ

Frequently asked questions

What is the difference between Standard and MinMax scaling?

Standard scaling (Z-Score) centers data at 0 with a variance of 1, ideal for algorithms that assume normally distributed features. MinMax compresses all values precisely between 0 and 1, ideal for neural networks and distance-based algorithms.

Are the computed scaling parameters returned for inverse transforms?

Yes. The JSON response includes the exact Mean and Std Dev (for Standard) or Min and Max (for MinMax) used to scale each column, enabling precise inverse transformations when needed.

Can it scale 10+ columns at once?

Absolutely. Pass a JSON array of all column names and they will all be scaled simultaneously in memory. The engine processes each column independently with its own computed metrics.