Use Native V8 with your AI.
Connect your account once and let the AI you already use work with it, without building another integration. Compute the exact Area Under the ROC Curve for binary classification predictions. Local, mathematically perfect, zero LLM estimation.
Developed, maintained, and hosted by Vinkius.
MCP VERIFIED · PRODUCTION READY · VINKIUS GUARANTEED
Waiting for input…
Works with modern AI clients that support MCP, including ChatGPT, Claude, Cursor, and more.
Complete set · 1 capability
The complete Native V8 capability set.
These are the exact actions your AI can choose when you ask it to work with Native V8.
01
1 capability in this set.
Part of 1 available through Native V8.
- 01
Calculate roc auc
Calculates the exact Area Under the ROC Curve (AUC) for binary classification
Observed, not estimated
870ms average. Fast in production.
Native V8 is checked daily against the live service.
- Fastest day
- 694ms
- Slowest day
- 1146ms
- 14-day trend
- Improving-6%
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.
https://edge.vinkius.com/vk_preview_VDeZcIBi8DFwURcnalpzs8zfvNkZF1ZSn2YpeI8w/mcpClaude Desktop
Follow the steps below to connect in seconds.
- 1In Claude Desktop, open Settings → Connectors.
- 2Click “Add custom connector” and paste the connector link above as the remote MCP server URL.
- 3Click Add and start a new chat — Native V8 capabilities are ready to use.
{
"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
FAQ
Questions Native V8 owners ask.
- 01
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.
- 02
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).
- 03
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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