MCP For Claude Marketplace
Grade-Tonnage Curve Model

Grade-Tonnage Curve Model MCP Connector for Claude

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Analyze resource models to generate grade-tonnage curves and calculate ore quantities.

4 tools Official Updated Oct 1, 2026 Official Vinkius Partner
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This MCP server provides tools to analyze mineral resource models by calculating the relationship between cut-off grades and resulting ore quantities. It allows for the generation of full grade-tonnage curves, calculation of tonnage, average grade, and contained metal, and the application of physical mining constraints like minimum mining width and maximum dilution. Use validate_resource_model to ensure model integrity before running get_curve_data or get_tonnage_stats.

miningresource-modeltonnagegrade-curvegeology

4 tools expose this connector's capabilities to your AI agent.

get_constrained_tonnage

Determines the maximum ore tonnage extractable given specific physical mining constraints

get_curve_data

Generates a set of data points to plot a full Grade-Tonnage curve

get_tonnage_stats

Calculates the fundamental relationship between a specific cut-off grade and the resulting resource quantities

validate_resource_model

Verifies the integrity and completeness of a resource model before attempting curve generation

See how to talk to your AI agent using Grade-Tonnage Curve Model.

What is the tonnage and average grade for resource model RM-101 at a 0.5 cut-off grade?

For resource model RM-101 at a 0.5 cut-off grade, the total tonnage is 1,250,000 tonnes with an average grade of 0.65%.

Generate a grade-tonnage curve for model M-500 using these cut-off grades: 0.1, 0.2, 0.3, 0.4, 0.5.

The curve data for model M-500 is: 0.1 cut-off: 5,000,000t @ 0.15%; 0.2 cut-off: 4,200,000t @ 0.22%; 0.3 cut-off: 3,100,000t @ 0.31%; 0.4 cut-off: 2,050,000t @ 0.42%; 0.5 cut-off: 1,100,000t @ 0.55%.

Calculate the constrained tonnage for RM-202 with a 0.4 cut-off and a minimum mining width of 5 meters.

Applying a minimum mining width of 5 meters to RM-202 at a 0.4 cut-off results in 850,000 tonnes of ore with an average grade of 0.48%.

You can use the `validate_resource_model` tool to verify the integrity and completeness of your resource model before performing calculations.

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