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Connect Roc Auc Evaluator to ChatGPT, Claude and Gemini

Set it up once and it works in ChatGPT, Claude, Cursor, and any other client you love. It all runs safely in the background, so you can relax and focus on what really matters. Stop letting your AI guess math and start getting exact results.

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

Your AI does the work. We keep it safe and sound.

No other AI tool gives you this. Your workflow runs in the client you already love, your account stays protected, and you decide what the agent can and cannot do. It is the whole reason to make the switch.

Each Connector lives inside our infrastructure, the same place where your workflow runs. The three things below are already part of it, working quietly in the background so you never have to think about them. Nothing to add, nothing to set up, nothing to worry about.

A futuristic MCP client docking bay
V8 Isolate01

Each Connector runs inside its own sealed environment.

Each Connector runs inside its own sealed V8 runtime — no access to your files, your system, or other servers. A Connector never sees past its own request.

Kill Switch02

One switch stops every agent. Instantly.

One action deactivates every Connector, revokes every token, and ends every session at once. AI Governance keeps the record.

FinOps per User03

Spending limits that pause instead of surprise.

Every user keeps their own connections and credentials, isolated from everyone else. Anything that would cross your spending limit is held for your approval, not billed.

Three controls, built into the layer your AI connects through.

Curated set · 1 capability

We ship only the actions that matter.

Capability set01 / 01

01

1 capability in this set.

Part of 1 available through Native V8.

  1. 01

    Calculate roc auc

    This capability calculates the exact Area Under the ROC Curve for binary classification tasks. It processes your probability arrays and true labels to return a mathematically precise AUC score.

Real work

What teams actually run

01

Model Validation

Verify the accuracy of a binary classifier by calculating its AUC score from test data.

02

Comparative Analysis

Determine which of two models is superior by comparing their exact AUC metrics on the same dataset.

03

Baseline Testing

Check if a model's performance is statistically better than a random guess by verifying if the AUC is above 0.5.

04

Automated Reporting

Use your AI agent to generate precise performance metrics as part of a larger data analysis workflow.

Automate a task

Put Native V8 to work on one thing.

Step-by-step automations your AI runs through this Connector: the workflow, the prompts to start with, and the exact capabilities behind each move.

One connector, every AI

Native V8 works with the most popular AI clients.

These are the most popular clients, each with a step-by-step guide: one link, set up once, with governance and visibility built in. And because everything runs on the MCP standard, the same connection also works in any other compatible client — nothing to rebuild.

ClaudeClaudeChatGPTChatGPTGeminiGeminiPerplexityPerplexityGrokGrokMicrosoft CopilotMicrosoft CopilotCursorCursorVS CodeVS CodeWindsurfWindsurfJetBrainsJetBrainsClineClineLangChainLangChainVercel AI SDKVercel AI SDKLovableLovableZ.aiZ.aiRaycastRaycastQwen CodeQwen CodeKimi CodeKimi CodeLe ChatLe Chat

Building your own app? The connector is yours to use.

You don't need a client to put Native V8 to work: the same hosted connection plugs into your own applications and agent code, with the same governance on every request. Build with it, chat with it — one connection for both.

Observed, not estimated

843ms average. Fast in production.

Native V8 is checked daily against the live service.

Daily averagePeak 1003ms
Oct 3Today
Fastest day
628ms
Slowest day
1003ms
14-day trend
Improving-17%

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 Native V8, so you can see the experience inside your AI.

It does not authenticate your account with Native V8. Actions requiring credentials or live account data may not run until you activate the Connector and authorize the service.

Native V8 Connector

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

Connector linkhttps://edge.vinkius.com/vk_preview_VDeZcIBi8DFwURcnalpzs8zfvNkZF1ZSn2YpeI8w/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 — Native V8 capabilities are ready to use.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "roc-auc-evaluator-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_VDeZcIBi8DFwURcnalpzs8zfvNkZF1ZSn2YpeI8w/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

Guided setup for Claude? Set up Native V8 in Claude and other AIs

See all the AI clients this connector works with ↑

Who it's for

Built for the work Native V8 owners hand off.

Data scientists and machine learning engineers who need to validate model performance without manual coding.

  • 01

    Data Scientist

    Hands off probability arrays and true labels to the MCP to get instant, reliable metrics.

  • 02

    ML Engineer

    Uses the capability to quickly verify if a new model iteration outperforms a previous version.

  • 03

    Researcher

    Relies on the exact mathematical output to ensure model evaluations are scientifically sound.

FAQ

Questions Native V8 owners ask.

  • 01

    Why can't my AI just calculate the AUC itself?

    LLMs are not built for iterative mathematical integration. They tend to estimate or guess, whereas this MCP uses the trapezoidal rule to provide an exact result.

  • 02

    What kind of models can I evaluate with this MCP?

    This MCP is designed specifically for binary classification models where you have predicted probabilities and true binary outcomes.

  • 03

    Which AI clients can I use with this MCP?

    You can use this with any MCP-compatible client, including Claude, Cursor, Windsurf, and VS Code.

  • 04

    Is the calculation performed locally?

    Yes, the math is offloaded to a local Node.js process to ensure mathematical rigor and speed.

  • 05

    How do I know the AUC score is accurate?

    The MCP uses the trapezoidal rule, which is a standard, mathematically exact method for calculating the area under a curve.

  • 06

    Why is calculating AUC difficult for LLMs?

    AUC requires sorting an array of probabilities, stepping through each threshold, and integrating the True Positive Rate over the False Positive Rate. LLMs cannot perform reliable array sorting or integral math.

  • 07

    What format should the probabilities be in?

    Provide a JSON array of actual labels (0 or 1) and a matching JSON array of predicted probabilities (floats between 0.0 and 1.0).

  • 08

    Is this identical to Python's scikit-learn AUC?

    Yes, it uses the identical trapezoidal rule approach to compute the area under the curve deterministically.

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