# Classification Efficiency Model AI Agent Connect

> Classification Efficiency Model MCP provides the mathematical heavy lifting for mineral processing. Your AI client uses this to model partition curves, evaluate separation quality, and forecast how hydrocyclones or screens will behave under specific conditions.

## Overview
- **Category:** engineering
- **Price:** Free
- **Endpoint:** https://edge.vinkius.com/vk_preview_5pNTjDgbH4eCuHno2KPr05OCaMrerZ9GQLBiCKj9/ai-agent-connect
- **Tags:** hydrocyclone, particle-size, mineral-processing, classification, modeling

## Description

You can now bring advanced particle separation modeling directly into your AI workflow. This MCP gives your agent the ability to handle the complex math required for mineral processing and classification. Instead of manually calculating distributions, you can ask your AI client to model the impact of the fish hook effect or predict how a specific feed will split between underflow and overflow streams. It handles the probability distributions for particle recovery and calculates the sharpness and efficiency of your classification circuits. Whether you are troubleshooting a hydrocyclone or designing a new screening setup, this MCP turns your agent into a specialized process engineering tool.

## Tools

### analyze_partition_curve
This tool generates the probability distribution for particle recovery across various sizes.

### calculate_separation_metrics
Use this to evaluate classification quality based on your feed and partition data.

### predict_equipment_performance
This tool forecasts the resulting size distribution for both underflow and overflow streams.

### simulate_fish_hook_impact
This tool predicts how the fish hook effect changes the expected recovery of fine particles.

## Prompt Examples

**Prompt:** 
```
Generate a partition curve for a cut size of 50 microns, a sharpness index of 1.5, and a bypass fraction of 0.1.
```

**Response:** 
```
The generated partition curve shows a probability distribution centered around the 50 micron cut size, adjusted for the 0.1 bypass fraction.
```

**Prompt:** 
```
What happens to the recovery if there is a fish hook effect at 20 microns with a magnitude of 0.05?
```

**Response:** 
```
The adjusted curve shows an increased recovery of fine particles near the 20 micron size due to the specified deviation.
```

**Prompt:** 
```
Calculate the separation metrics for a feed distribution and a specific partition curve.
```

**Response:** 
```
The calculated metrics show a sharpness of 1.4, a bypass of 0.08, and an overall efficiency of 85%.
```

## Capabilities

### Partition Curve Generation
Your agent creates probability distributions for particle recovery across size ranges.

### Separation Quality Assessment
The AI calculates sharpness and efficiency metrics from feed and partition data.

### Stream Distribution Forecasting
Your agent predicts the size distributions for underflow and overflow streams.

### Fish Hook Modeling
The AI simulates how the fish hook effect alters fine particle recovery.

## Use Cases

### Hydrocyclone Optimization
Predict how changes in feed will affect the underflow and overflow size distributions.

### Screening Performance Analysis
Evaluate the efficiency of screen separation using partition curve data.

### Fine Particle Recovery Modeling
Simulate the fish hook effect to see how it impacts the recovery of small particles.

### Circuit Design Verification
Use predicted stream distributions to validate new classification equipment setups.

## Benefits

- Automates the calculation of partition curves and probability distributions.
- Predicts equipment performance without manual mathematical modeling.
- Models specific deviations like the fish hook effect on fine particle recovery.
- Provides immediate efficiency and sharpness metrics for classification circuits.

## How It Works

Connecting this MCP to your AI client gives your agent immediate access to specialized engineering math.

1. Connect your AI client to the Vinkius hosted MCP.
2. Provide your process data or specific parameters to your agent.
3. The agent calls the necessary mathematical tools.
4. Your agent delivers the calculated curves, metrics, or predictions.

## Frequently Asked Questions

**What equipment can this MCP model?**
This MCP is designed for modeling hydrocyclones and screens used in particle separation.

**Can I use this with Claude or Cursor?**
Yes, you can connect this MCP to any MCP-compatible client including Claude, Cursor, and Windsurf.

**What is the fish hook effect simulation?**
The simulate_fish_hook_impact tool predicts how this specific effect alters the recovery of fine particles in your model.

**Does this MCP handle stream distributions?**
Yes, the predict_equipment_performance tool forecasts the size distribution for both underflow and overflow streams.

**How do I get separation metrics?**
You can use the calculate_separation_metrics tool to evaluate quality based on your feed and partition data.