MCP For Claude Marketplace
Flotation Kinetics Modeler

Flotation Kinetics Modeler MCP Connector for Claude

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Models flotation kinetics from test data to predict recovery and residence time.

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

This MCP server provides specialized tools for mineral processing engineers to model flotation kinetics. By analyzing recovery-time datasets, users can determine fundamental kinetic constants using calculate_kinetic_parameters. The server also allows for predicting future recovery levels with predict_recovery, calculating necessary circuit times via estimate_residence_time, and simulating process changes through simulate_condition_impact.

flotationkineticsmineral-processingrecovery-predictionprocess-modeling

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

calculate_kinetic_parameters

Determines the fundamental kinetic constants from experimental recovery-time datasets

estimate_residence_time

Calculates the required time in the flotation circuit to meet a specific recovery target

predict_recovery

Predicts the expected recovery percentage at a specific point in time

simulate_condition_impact

Evaluates how changing flotation conditions affects the kinetics

See how to talk to your AI agent using Flotation Kinetics Modeler.

Calculate the kinetic parameters for this data: [{'time': 1, 'recovery': 10}, {'time': 5, 'recovery': 40}, {'time': 10, 'recovery': 65}] using first-order kinetics.

The calculated rate constant is 0.15 and the ultimate recovery is 85.2%.

If my rate constant is 0.2 and ultimate recovery is 90%, what will the recovery be at 15 minutes using first-order kinetics?

The predicted recovery at 15 minutes is 78.5%.

How much time is needed to reach 70% recovery if the rate constant is 0.12 and ultimate recovery is 80%?

The required residence time to achieve 70% recovery is 12.4 minutes.

You can use the `calculate_kinetic_parameters` tool by providing your recovery-time dataset as a JSON array.

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