MCP For Claude Marketplace
Blending Optimization Mining

Blending Optimization Mining MCP Connector for Claude

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Optimize ore blending using linear programming to meet grade constraints and maximize value.

4 tools Official Updated Oct 1, 2026 Official Vinkius Partner
More Details Connect to Claude

This MCP server provides advanced mathematical tools for metallurgical blending. It allows AI agents to solve complex linear programming problems to find the most efficient combination of ore sources. By using get_source_availability, agents can inspect current stockpiles, and with calculate_optimal_blend, they can generate precise recipes that satisfy specific grade constraints for mass and quality. It also includes validate_blend_feasibility to check if a target is achievable and predict_blend_quality to forecast the chemical composition of a proposed mix.

oreblendinglinear-programmingmetallurgymining-optimization

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

get_source_availability

Retrieves current stock levels and quality profiles for all available ore stockpiles

predict_blend_quality

Calculates the expected chemical composition of a blend given a specific allocation of ore masses

validate_blend_feasibility

Quickly checks if a specific combination of ore sources can theoretically meet the required grade constraints

calculate_optimal_blend

Solves the linear programming problem to find the most efficient combination of ore sources to meet grade constraints

See how to talk to your AI agent using Blending Optimization Mining.

Find the best blend for 5000 tons of ore with at least 62% Iron and max 0.05% Phosphorus using available sources.

The optimal recipe for 5000 tons is: Source_A (3200 tons) and Source_B (1800 tons), resulting in 62.5% Iron and 0.04% Phosphorus.

Is it possible to blend 1000 tons of ore with 65% Iron using the current stockpiles?

No, the current stockpiles cannot reach a 65% Iron concentration for a 1000 ton mass; the maximum achievable is 63.8%.

What will the quality be if I mix 2000 tons of Source_A and 3000 tons of Source_C?

The predicted blend will have a total mass of 5000 tons with an Iron grade of 61.2% and Silica content of 4.5%.

You can use the `calculate_optimal_blend` tool to find the most efficient combination of sources based on your target mass and grade constraints.

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