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Connect Silhouette Score 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. Verify your data groupings with precise geometric distance metrics.

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 silhouette score

    This capability computes the Silhouette score for a given set of 2D array data and cluster labels. It provides a mathematical metric to evaluate how well your data is partitioned.

Real work

What teams actually run

01

K-Means Tuning

An agent compares Silhouette scores across multiple K values to pick the most efficient grouping.

02

Embedding Analysis

You provide customer embeddings to the agent to check if the resulting clusters are distinct enough for segmentation.

03

Automated Model Validation

The agent runs a score check on new data to ensure clustering stability hasn't degraded.

04

Cluster Overlap Detection

Use the score to identify when clusters are too close together and require better feature engineering.

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

836ms average. Fast in production.

Native V8 is checked daily against the live service.

Daily averagePeak 939ms
Oct 3Today
Fastest day
622ms
Slowest day
939ms
14-day trend
Stable-2%

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_J0AXoXdn74cbRlNPvFSkKw2q9Axxs9X8l7Bx5A0x/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": {
    "silhouette-score-engine-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_J0AXoXdn74cbRlNPvFSkKw2q9Axxs9X8l7Bx5A0x/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 use this MCP to add a layer of mathematical validation to their agentic workflows.

  • 01

    Data Scientist

    Hands off raw cluster labels and coordinates to the agent to verify model performance.

  • 02

    ML Engineer

    Uses the agent to automate the search for the best K value in clustering pipelines.

  • 03

    Data Analyst

    Validates the statistical significance of data groupings before presenting findings.

FAQ

Questions Native V8 owners ask.

  • 01

    How does this MCP handle complex math?

    It uses native V8 JavaScript to perform Euclidean distance calculations, which avoids the mathematical errors common in standard LLM reasoning.

  • 02

    Can I use this with K-Means?

    Yes. This MCP is specifically designed to evaluate the quality of clustering algorithms like K-Means by measuring cluster cohesion.

  • 03

    What kind of data does it accept?

    The capability accepts 2D array data and the corresponding cluster labels.

  • 04

    Which AI clients can use this MCP?

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

  • 05

    Does this replace my clustering algorithm?

    No. This MCP is an evaluation capability that measures how well your existing clustering algorithms have performed.

  • 06

    What does a good Silhouette score look like?

    Scores range from -1 to 1. A score close to 1 means clusters are well separated and dense. A score near 0 means overlapping clusters, and negative means points were assigned to the wrong cluster.

  • 07

    Does it support high-dimensional data?

    Yes. It computes N-dimensional Euclidean distance, so it can handle 2D points, 3D coordinates, or multi-feature data vectors.

  • 08

    Why not use Python?

    Vinkius edge runtime avoids the cold-start and infrastructure overhead of Python servers, executing instantly in the local Agent environment.

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