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ClaudeChatGPTPerplexityGeminiMicrosoft CopilotRaycastMeta AIGrokZ.aiQwenKimi
DeepSeekMistralCursorVS CodeWindsurfJetBrainsClineLovableVercel AI SDKLangChain

Use Kriging Estimation Model with your AI.

Connect your account once and let the AI you already use work with it, without building another integration. Perform Ordinary Kriging to estimate block grades and spatial uncertainty.

Included with plan

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

Complete set · 4 capabilities

The complete Kriging Estimation Model capability set.

These are the exact actions your AI can choose when you ask it to work with Kriging Estimation Model.

Capability set01 / 01

01-04

4 capabilities in this set.

Part of 4 available through Kriging Estimation Model.

  1. 01

    Get block estimates

    Calculates the estimated grade and uncertainty for a specific set of block discretization points

  2. 02

    Get kriging weights

    Retrieves the specific influence (weights) each sample has on a target estimation point

  3. 03

    Get spatial correlation stats

    Provides high-level summary statistics regarding the density and distribution of samples within the search space

  4. 04

    Validate variogram parameters

    Ensures the variogram model provided is physically and mathematically sound for kriging

One connector, every AI

Kriging Estimation Model 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 Kriging Estimation Model 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.

Connect your client

One URL. Every client.

Activate the Connector, copy your link, and paste it into the client you already use. 4 capabilities arrive 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 Kriging Estimation Model, so you can see the experience inside your AI.

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

Kriging Estimation Model Connector

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

Connector linkhttps://edge.vinkius.com/vk_preview_bpI2P6MJOkCMUP4nkuIhdrCAeup3yh2mTroa3jHJ/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 — Kriging Estimation Model capabilities are ready to use.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "kriging-estimation-model-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_bpI2P6MJOkCMUP4nkuIhdrCAeup3yh2mTroa3jHJ/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? link.label

See all the AI clients this connector works with ↑

FAQ

Questions Kriging Estimation Model owners ask.

  • 01

    What is Ordinary Kriging?

    Ordinary Kriging is a geostatistical interpolation method that estimates values at unsampled locations by weighting nearby known samples based on spatial correlation.

  • 02

    How do I ensure my variogram model is valid?

    You can use the validate_variogram_parameters capability to check if your nugget, sill, and range parameters are mathematically sound.

  • 03

    Can this model handle directional dependencies?

    Yes, the model accounts for anisotropy and uses a search ellipse to define the spatial boundary for sample selection.

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