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Connect Confusion Matrix Engine to ChatGPT and Claude

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. Get mathematically perfect evaluation scores without LLM hallucinations.

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 confusion matrix

    This capability computes an exact confusion matrix and accuracy score. You pass in arrays of actual and predicted labels to get the results.

Real work

What teams actually run

01

Model Validation

Verify the precision and recall of a newly trained classifier using actual vs predicted arrays.

02

Bias Detection

Identify if a model is disproportionately predicting one class over another by analyzing the confusion matrix.

03

Error Analysis

Pinpoint exactly how many False Positives or False Negatives a model is producing.

04

Automated Benchmarking

Use your agent to run repetitive metric calculations on large sets of classification data.

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

775ms average. Fast in production.

Native V8 is checked daily against the live service.

Daily averagePeak 957ms
Oct 3Today
Fastest day
582ms
Slowest day
957ms
14-day trend
Slowing+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.

Connector linkhttps://edge.vinkius.com/vk_preview_lcKPfQMdEs9vOL0QvMD7tp5xcmCCFVUKYwiOuwlI/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": {
    "confusion-matrix-engine-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_lcKPfQMdEs9vOL0QvMD7tp5xcmCCFVUKYwiOuwlI/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.

This MCP is built for professionals who need to validate machine learning model performance without manual calculation errors.

  • 01

    Data Scientists

    They hand off label arrays to the agent to get verified performance metrics.

  • 02

    Machine Learning Engineers

    They use the capability to quickly check for model bias or classification errors.

  • 03

    AI Researchers

    They rely on the deterministic output to ensure their evaluation datasets are processed accurately.

FAQ

Questions Native V8 owners ask.

  • 01

    Why should I use this instead of just asking my AI?

    LLMs are probabilistic and often hallucinate math. This MCP uses a deterministic runtime to ensure the numbers are mathematically perfect.

  • 02

    What metrics does this MCP calculate?

    It calculates the confusion matrix, accuracy, True Positives, True Negatives, False Positives, False Negatives, Precision, Recall, and F1-Score.

  • 03

    Which AI clients can use this MCP?

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

  • 04

    Do I need to host this myself?

    No. Vinkius hosts and manages the MCP for you. You just connect your client and start using the capabilities.

  • 05

    How does it handle large datasets?

    The engine uses a local JavaScript runtime to process the arrays you provide, ensuring the math remains accurate regardless of the label count.

  • 06

    Why not let Claude/GPT calculate the accuracy?

    LLMs operate on tokens and probability distributions. If you give them 500 predictions, they might summarize or estimate the F1-score rather than calculating it exactly. This engine ensures 100% mathematical precision.

  • 07

    Does it support multi-class classification?

    Yes, the engine automatically detects unique labels from both arrays and constructs an N-by-N confusion matrix, handling both binary and multiclass evaluations flawlessly.

  • 08

    Is there a limit to the array size?

    The only limit is the standard Context Window limit for transmitting the JSON arrays. For arrays exceeding 100k items, consider chunking or local CSV aggregators.

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