MCP For Claude Marketplace
Destemming & Crushing Efficiency

Destemming & Crushing Efficiency MCP Connector for Claude

A+

Calculate throughput, stem removal, and berry damage for winemaking machinery.

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

This MCP server provides precise calculations for the destemming and crushing stage of vinification. It helps winemakers optimize machine performance by analyzing how grape variety and cluster morphology affect processing. Use get_current_throughput to monitor real-time mass flow, analyze_stem_removal to evaluate stem detachment efficiency, and calculate_berry_damage to predict breakage. You can also use optimize_machine_settings to find the ideal balance between roller spacing and drum speed for your specific target damage rate.

viticulturevinificationthroughputmachine-optimizationgrape-processing

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

analyze_stem_removal

Evaluate how effectively the machine is separating stems from the fruit

calculate_berry_damage

Predict the percentage of berry breakage based on machine settings

get_current_throughput

Determine the actual mass of grapes being processed per hour

optimize_machine_settings

Recommend ideal roller spacing and drum speed to meet a target damage rate

See how to talk to your AI agent using Destemming & Crushing Efficiency.

What is the current throughput for a Cabernet Sauvignon with a 5kg cluster weight and 2% MOG at 1000kg/h capacity?

The actual throughput is 945 kg/h with an Optimal efficiency rating.

Predict the berry damage for Pinot Noir with 4kg clusters, 15mm roller spacing, and 30 drum speed at a 10% target damage rate.

The predicted berry breakage is 12%, with a juice loss of 3% and a deviation of 2% from your target.

Recommend settings for Merlot with 6kg clusters to hit a 5% damage rate.

The recommended settings are 18mm roller spacing and 25 drum speed, with a predicted efficiency of 0.85.

Different varieties have different cluster morphologies. The tools use this data to adjust throughput and stem removal predictions, as compact clusters resist detachment more than loose ones.

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