Native V8 Connector for AI agents.
1 live capability
Validate clustering quality and find the best K-means groupings with precise math.
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Why people use Native V8
Silhouette Score Engine for K-Means Clustering Validation
This Connector cuts out the manual math. You just give your agent the data and the labels, and it returns the Silhouette score immediately. You get a clear, numerical confirmation of your model's quality without ever leaving your chat interface.
What Vinkius changes
Your agent gets the math it needs to prove your data groupings are actually valid.
Use it from Claude, ChatGPT, Cursor or another AI client you already have.
One account · 5,900+ Connectors
- Real-world use case 01
Customer Segmentation Validation
A marketing analyst wants to see if 5 customer segments are too crowded.
- Real-world use case 02
Automated K-Means Tuning
A developer wants to find the best K for a new dataset.
- Real-world use case 03
Spatial Analysis Check
A researcher needs to know if geographic data points are grouped logically.
Complete set · 1capability
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 Capability
Calculate silhouette score
Takes your 2D data and labels to output a precise Silhouette score for clustering evaluation. It provides a clear metric for group cohesion.
Set up in minutes
One URL. Then ask Native V8 to work.
Claude and ChatGPT only need the Connector URL. Copy it once, add it in settings, and use Native V8 from the conversation.
Choose your client
Live previewAdvanced clients IDE · CLI
Claude · Web + desktop
Connector URL · ready to paste
Streamable HTTPhttps://edge.vinkius.com/vk_preview_J0AXoXdn74cbRlNPvFSkKw2q9Axxs9X8l7Bx5A0x/mcp - Step 01
Open Connectors
In Claude Web or Claude Desktop, open Settings and choose Connectors.
- Step 02
Add the URL
Choose Add custom connector, name it Native V8, and paste the URL above.
- Step 03
Turn it on in chat
Select +, open Connectors, and enable Native V8 for the conversation.
ChatGPT · Web + desktop
Connector URL · ready to paste
Streamable HTTPhttps://edge.vinkius.com/vk_preview_J0AXoXdn74cbRlNPvFSkKw2q9Axxs9X8l7Bx5A0x/mcp - Step 01
Open MCP settings
On desktop, open Settings and MCP servers. On web, open your workspace app or connector settings.
- Step 02
Add the URL
Choose Add server with Streamable HTTP, or create a custom MCP app, then paste the Native V8 URL.
- Step 03
Save and start
Save the connection and enable Native V8 in your conversation. Desktop may ask you to restart once.
Cursor · IDE configuration
Advanced setup
{
"mcpServers": {
"silhouette-score-engine": {
"url": "https://edge.vinkius.com/vk_preview_J0AXoXdn74cbRlNPvFSkKw2q9Axxs9X8l7Bx5A0x/mcp"
}
}
}- Step 01
Open MCP Settings
Press Cmd+Shift+P (macOS) or Ctrl+Shift+P (Windows/Linux) → search "MCP Settings"
- Step 02
Add the server config
Paste the JSON configuration above into the mcp.json file that opens
- Step 03
Save the file
Cursor will automatically detect the new Connector
- Step 04
Start using Native V8
Open Agent mode in chat and ask: "Using Native V8, help me...". 1 tools available
VS Code Copilot · IDE configuration
Advanced setup
{
"mcpServers": {
"silhouette-score-engine": {
"url": "https://edge.vinkius.com/vk_preview_J0AXoXdn74cbRlNPvFSkKw2q9Axxs9X8l7Bx5A0x/mcp"
}
}
}- Step 01
Create MCP config
Create a .vscode/mcp.json file in your project root
- Step 02
Add the server config
Paste the JSON configuration above
- Step 03
Enable Agent mode
Open GitHub Copilot Chat and switch to Agent mode using the dropdown
- Step 04
Start using Native V8
Ask Copilot: "Using Native V8, help me...". 1 tools available
Windsurf · IDE configuration
Advanced setup
{
"mcpServers": {
"silhouette-score-engine": {
"url": "https://edge.vinkius.com/vk_preview_J0AXoXdn74cbRlNPvFSkKw2q9Axxs9X8l7Bx5A0x/mcp"
}
}
}- Step 01
Open MCP Settings
Go to Settings → MCP Configuration or press Cmd+Shift+P and search "MCP"
- Step 02
Add the server
Paste the JSON configuration above into mcp_config.json
- Step 03
Save and reload
Windsurf will detect the new server automatically
- Step 04
Start using Native V8
Open Cascade and ask: "Using Native V8, help me...". 1 tools available
Cline · IDE configuration
Advanced setup
{
"mcpServers": {
"silhouette-score-engine": {
"url": "https://edge.vinkius.com/vk_preview_J0AXoXdn74cbRlNPvFSkKw2q9Axxs9X8l7Bx5A0x/mcp"
}
}
}- Step 01
Open Cline MCP Settings
Click the Connectors icon in the Cline sidebar panel
- Step 02
Add remote server
Click "Add Connector" and paste the configuration above
- Step 03
Enable the server
Toggle the server switch to ON
- Step 04
Start using Native V8
Ask Cline: "Using Native V8, help me...". 1 tools available
Claude Code · Terminal command
Advanced setup
claude mcp add silhouette-score-engine --transport http "https://edge.vinkius.com/vk_preview_J0AXoXdn74cbRlNPvFSkKw2q9Axxs9X8l7Bx5A0x/mcp"- Step 01
Install Claude Code
Run npm install -g @anthropic-ai/claude-code if not already installed
- Step 02
Add the Connector
Run the command above in your terminal
- Step 03
Verify the connection
Run claude mcp to list connected servers, or type /mcp inside a session
- Step 04
Start using Native V8
Ask Claude: "Using Native V8, show me...". 1 tools are ready
Where the request belongs
Work Native V8 can move forward.
Data scientists who are tired of guessing cluster quality and ML engineers who need to automate hyper-parameter selection.
Machine Learning Engineer
Validates clustering models during automated hyper-parameter tuning on a Tuesday afternoon.
Data Analyst
Checks if customer segments are actually distinct and not overlapping before presenting to stakeholders.
Research Scientist
Evaluates the mathematical validity of spatial data groupings for academic publications.
Build the capability set
Add more capabilities.
Each Connector adds new actions and data without changing how you work.
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Group complex data points into optimal clusters with deterministic, high-speed Euclidean K-Means classification.
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PCA Dimensionality Engine
Perform native Principal Component Analysis to safely reduce high-dimensional datasets without losing critical variance.
ROC AUC Evaluator
Compute the exact Area Under the ROC Curve for binary classification predictions. Local, mathematically perfect, zero LLM estimation.
Embedding Similarity Calculator
Calculate mathematical distances and similarity scores between multidimensional numerical vectors.
Graph Analysis Toolkit
Deep structural analysis of directed and undirected graphs, providing metrics on connectivity, topology, and node importance.
Bring your own AI
Change the model, client or framework. Keep Native V8 connected.
-
Claude -
ChatGPT -
Gemini -
Cursor -
VS Code -
Windsurf -
ZCode -
Cline -
Zed -
Continue -
Kiro -
Roo Code -
Zencoder -
Goose -
Void -
Augment Code -
Amp -
Qodo -
Tabnine -
Pieces -
Sourcegraph Cody -
JetBrains -
Warp -
Amazon Q -
Antigravity -
BoltAI -
Raycast -
Jan -
LM Studio -
AnythingLLM -
Open WebUI -
Msty -
Cherry Studio -
LibreChat -
TypingMind -
Chorus -
5ire -
n8n -
LangChain -
LlamaIndex -
CrewAI -
Vercel AI SDK
Before you connect
Questions about Native V8.
The practical details behind the request, access and result.
Can the Silhouette Score Engine help me pick the best K for K-Means?
Yes. It calculates scores for different K values so your agent can compare them and pick the best one for your specific dataset.
What kind of data does the Silhouette Score Engine need?
It works with 2D array data and the labels you've assigned to those points during your clustering process.
Does this Connector replace my machine learning model?
No, it evaluates the results of your model. You still need your clustering algorithm to generate the labels first.
Is the math accurate?
Yes, it uses native V8 JavaScript to perform the geometric calculations for perfect precision.
How does this help with customer segmentation?
It gives you a score showing how well-separated your customer groups are, helping you avoid overlapping segments before you launch a campaign.
Can I use this for 3D data?
The current capability is designed for 2D coordinate arrays to calculate cohesion scores.
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.
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.
Why not use Python?
Vinkius edge runtime avoids the cold-start and infrastructure overhead of Python servers, executing instantly in the local Agent environment.
One connection away
Give your agent a direct line to Native V8.
Connect Native V8 once. Keep it beside 5,900+ managed Connectors when the next task needs more.
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