# Wine Allocations Management AI Agent Connect

> Optimized distribution planning for finite wine inventory across sales channels.

## Overview
- **Category:** inventory-management
- **Price:** Free
- **Endpoint:** https://edge.vinkius.com/vk_preview_sZMD3KgPDMdrhlUMZ5HyA7A4n7CfiMVn3qpVhjMy/ai-agent-connect
- **Tags:** wine, inventory, optimization, distribution, logistics

## Description

This MCP server provides a specialized optimization engine for distributing limited wine inventory. It balances margin targets against customer loyalty and historical growth requirements using advanced fairness constraints. Use `get_allocation_plan` to generate optimized distribution plans, `get_channel_performance_forecast` to predict commercial outcomes, `validate_growth_feasibility` to check growth targets, and `get_allocation_rationale` to understand the logic behind specific channel allocations.

## Tools

### get_allocation_plan
Generates the primary optimized distribution plan for a specific wine product

### get_allocation_rationale
Provides a human-readable explanation for why a specific channel received its specific allocation

### get_channel_performance_forecast
Predicts the likely commercial outcome of an allocation for a specific channel

### validate_growth_feasibility
Checks if a proposed growth target for a channel is realistic

## Prompt Examples

**Prompt:** 
```
Generate an allocation plan for wine 'CHATEAU-2023' with 5000 units available. Channel A wants 3000 units with loyalty 0.8, and Channel B wants 4000 units with loyalty 0.5. Target margin is 0.25.
```

**Response:** 
```
The optimized plan allocates 3250 units to Channel A and 1750 units to Channel B to satisfy the margin target and fairness constraints.
```

**Prompt:** 
```
What is the expected sell-through for 500 units of 'CHATEAU-2023' in the 'Retail' channel?
```

**Response:** 
```
The expected sell-through for 500 units in the Retail channel is 85%.
```

**Prompt:** 
```
Explain why Channel B received 1750 units in the recent allocation plan.
```

**Response:** 
```
Channel B received 1750 units because the fairness constraint ensured a baseline volume was maintained despite its lower loyalty score compared to Channel A.
```

## Frequently Asked Questions

**How does the engine decide the allocation for each channel?**
The engine uses `get_allocation_plan` to calculate volumes by weighing channel loyalty scores and margin targets while applying fairness constraints to ensure all channels maintain a baseline presence.

**Can I predict the revenue for a specific channel?**
Yes, you can use `get_channel_performance_forecast` to obtain projected revenue, margin, and expected sell-through for a given volume.

**How can I verify if a growth request is realistic?**
You can use the `validate_growth_feasibility` tool to check if a target growth percentage is achievable based on historical data and current constraints.