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ClaudeChatGPTPerplexityGeminiMicrosoft CopilotRaycastMeta AIGrokZ.aiQwenKimi
DeepSeekMistralCursorVS CodeWindsurfJetBrainsClineLovableVercel AI SDKLangChain

Use Resource Model Validation with your AI.

Connect your account once and let the AI you already use work with it, without building another integration. Validate mineral resource block models using statistical analysis and spatial swath plots.

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 Resource Model Validation capability set.

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

Capability set01 / 01

01-04

4 capabilities in this set.

Part of 4 available through Resource Model Validation.

  1. 01

    Calculate validation metrics

    Computes advanced error metrics to quantify model quality

  2. 02

    Detect local bias

    Identifies specific geographic areas where the model is significantly overestimating or underestimating

  3. 03

    Generate swath analysis

    Evaluates the spatial accuracy of the model by comparing averages along a chosen axis

  4. 04

    Get statistical summary

    Provides a high-level comparison of the globalThis averages between the model and the samples

One connector, every AI

Resource Model Validation 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 Resource Model Validation 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 Resource Model Validation, so you can see the experience inside your AI.

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

Resource Model Validation Connector

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

Connector linkhttps://edge.vinkius.com/vk_preview_iZvzoUDDLKeVTunIMJpIhGxIDj9sJ3irnWTaI1wJ/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 — Resource Model Validation capabilities are ready to use.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "resource-model-validation-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_iZvzoUDDLKeVTunIMJpIhGxIDj9sJ3irnWTaI1wJ/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 Resource Model Validation owners ask.

  • 01

    How can I check for systematic errors in my model?

    You can use calculate_validation_metrics to compute RMSE and mean error, or detect_local_bias to find specific geographic zones where the model deviates from sample data.

  • 02

    What is the purpose of swath analysis?

    The generate_swath_analysis capability evaluates spatial accuracy by comparing average grades along a chosen axis (X, Y, or Z) within defined slices.

  • 03

    Does this capability handle sampling bias?

    Yes, the get_statistical_summary capability includes an option to apply declustering weights to correct for sampling bias.

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