# Dry Bean Canning Quality Predictor AI Agent Connect

> Predicts canning yield, texture, and color retention for dry beans.

## Overview
- **Category:** agriculture
- **Price:** Free
- **Endpoint:** https://edge.vinkius.com/vk_preview_gOSDCRPRuQ6VMBkaqDQYFFT2IIh6o9pt21jH2lpa/ai-agent-connect
- **Tags:** canning, beans, quality-control, agriculture-tech, food-processing

## Description

This MCP server provides tools to simulate the canning process for dry beans. It uses seed characteristics like size, variety, and hydration coefficient to predict physical outcomes. Use `simulate_canning_process` to estimate yield and texture, `evaluate_canner_acceptance` to determine commercial status and pricing, `calculate_hydration_profile` for swelling analysis, and `check_coat_integrity` to assess the risk of seed coat failure.

## Tools

### calculate_hydration_profile
Analyzes how the specific variety and hydration coefficient will influence the swelling and weight of the beans

### check_coat_integrity
Assesses the risk of seed coat failure during the high-pressure canning process

### evaluate_canner_acceptance
Determines if a specific batch of beans meets commercial standards and the resulting financial impact

### simulate_canning_process
Predicts the physical state of the beans after the canning simulation is complete

## Prompt Examples

**Prompt:** 
```
Predict the canning quality for a medium-sized red kidney bean with a hydration coefficient of 0.85 and 5% hardseeds.
```

**Response:** 
```
The predicted yield is 92%, with a texture score of 8.5 and high color retention.
```

**Prompt:** 
```
Will a batch with a texture score of 7.5 and color retention of 0.9 be accepted at a premium price?
```

**Response:** 
```
Yes, the batch meets the high-quality thresholds and is awarded Premium status.
```

**Prompt:** 
```
Check the risk of seed coat failure for a large black bean variety with 12% hardseeds.
```

**Response:** 
```
The integrity score is 72, indicating a moderate risk level for the seed coat.
```

## Frequently Asked Questions

**How accurate are the canning predictions?**
Predictions are based on a specialized canning process simulation model that accounts for seed size, variety, and hardseed percentage.

**Can I determine if a batch will be accepted by canners?**
Yes, by using the `evaluate_canner_acceptance` tool with the results from the simulation, you can determine if a batch qualifies for Premium, Discount, or rejection status.

**What factors influence the texture score?**
The texture score is primarily influenced by the initial cooked texture rating and the hardseed percentage of the batch.