Bring Data Normalization
to Windsurf
Learn how to connect Feature Scaler Engine to Windsurf 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 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)
Deterministically Standardize (Z-Score) or MinMax Scale numeric columns offline
Why Windsurf?
Windsurf's Cascade agent chains multiple Feature Scaler Engine tool calls autonomously. query data, analyze results, and generate code in a single agentic session. Paste Vinkius Edge URL, reload, and all 1 tools are immediately available. Real-time tool feedback appears inline, so you see API responses directly in your editor.
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Windsurf's Cascade agent autonomously chains multiple tool calls in sequence, solving complex multi-step tasks without manual intervention
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Purpose-built for agentic workflows. Cascade understands context across your entire codebase and integrates MCP tools natively
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JSON-based configuration means zero code changes: paste a URL, reload, and all 1 tools are immediately available
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Real-time tool feedback is displayed inline, so you see API responses directly in your editor without switching contexts
Feature Scaler Engine in Windsurf
Feature Scaler Engine and 4,000+ other MCP servers. One platform. One governance layer.
Teams that connect Feature Scaler Engine to Windsurf 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 Feature Scaler Engine in Windsurf
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 Windsurf 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
Feature Scaler Engine for Windsurf
Every tool call from Windsurf to the Feature Scaler Engine MCP Server is protected by DLP redaction, cryptographic audit chains, V8 sandbox isolation, kill switch, and financial circuit breakers.
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.
How does Windsurf discover MCP tools?
Windsurf reads the mcp_config.json file on startup and connects to each configured server via Streamable HTTP. Tools are listed in the MCP panel and available to Cascade automatically.
Can Cascade chain multiple MCP tool calls?
Yes. Cascade is an agentic system. it can plan and execute multi-step workflows, calling several tools in sequence to accomplish complex tasks without manual prompting between steps.
Does Windsurf support multiple MCP servers?
Yes. Add as many servers as needed in mcp_config.json. Each server's tools appear in the MCP panel and Cascade can use tools from different servers in a single flow.
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