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ClaudeChatGPTPerplexityGeminiMicrosoft CopilotRaycastMeta AIGrokZ.aiQwenKimi
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Use ml-pca with your AI.

Connect your account once and let the AI you already use work with it, without building another integration. Perform native Principal Component Analysis to safely reduce high-dimensional datasets without losing critical variance.

Included with plan

Ask AI about this Connector

Developed, maintained, and hosted by Vinkius.

MCP VERIFIED · PRODUCTION READY · VINKIUS GUARANTEED

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Works with modern AI clients that support MCP, including ChatGPT, Claude, Cursor, and more.

ChatGPTClaudeCursorPerplexityGeminiMicrosoft CopilotRaycastMeta AI

Complete set · 1 capability

The complete ml-pca capability set.

These are the exact actions your AI can choose when you ask it to work with ml-pca.

Capability set01 / 01

01

1 capability in this set.

Part of 1 available through ml-pca.

  1. 01

    Calculate pca

    Calculates Principal Component Analysis (PCA) exactly to reduce dimensionality

Observed, not estimated

834ms average. Fast in production.

ml-pca is checked daily against the live service.

Daily averagePeak 1001ms
Aug 20Today
Fastest day
742ms
Slowest day
1001ms
14-day trend
Slowing+16%

Connect your client

One URL. Every client.

Activate the Connector, copy your link, and paste it into the client you already use. 1 capability arrives ready to run.

Preview access · not provider authentication

The vk_preview_* token belongs to Vinkius preview infrastructure. It lets Claude discover and display the capabilities of ml-pca, so you can see the experience inside your AI.

It does not authenticate your account with ml-pca. Actions requiring credentials or live account data may not run until you activate the Connector and authorize the service.

ml-pca Connector

You're all set. Choose your MCP client and follow the setup instructions.

Connector linkhttps://edge.vinkius.com/vk_preview_CTLJGZMOzWS3P0dPZpSvR6monLs0Y9Vip0jwJ7gT/mcp

Claude Desktop

Follow the steps below to connect in seconds.

  1. 1In Claude Desktop, open Settings → Connectors.
  2. 2Click “Add custom connector” and paste the connector link above as the remote MCP server URL.
  3. 3Click Add and start a new chat — ml-pca capabilities are ready to use.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "pca-dimensionality-engine-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_CTLJGZMOzWS3P0dPZpSvR6monLs0Y9Vip0jwJ7gT/mcp"
    }
  }
}
  • Claude
  • ChatGPT
  • Cursor
  • VS Code
  • Windsurf
  • Claude Code
  • JetBrains
  • Cline

Step-by-step instructions for each client are in the guide. How to connect

FAQ

Questions ml-pca owners ask.

  • 01

    Does it guarantee exact mathematical precision?

    Absolutely. It utilizes native V8 singular value decomposition algorithms to compute eigenvectors without any probabilistic hallucination.

  • 02

    How does it handle explained variance?

    The engine automatically returns an array detailing the exact percentage of total dataset variance preserved by each calculated component.

  • 03

    Can it process large embedding vectors?

    Yes, it is highly optimized to instantly compress complex, multi-dimensional embedding matrices generated by modern AI models.

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