# BTX Extraction Designer AI Agent Connect

> BTX Extraction Designer MCP handles the heavy lifting for Benzene, Toluene, and Xylene separation. It gives your AI client the ability to evaluate feedstock, pick the right solvents, size extraction columns, and predict how much product you'll actually recover from a given stream.

## Overview
- **Category:** process-design
- **Price:** Free
- **Endpoint:** https://edge.vinkius.com/vk_preview_oYhAAzml3fd1iu7cKOCRBGz8bKOp0jHtIULFmoBZ/ai-agent-connect
- **Tags:** btx, extraction, aromatics, solvent-selection, refinery

## Description

You can now run complex aromatic separation calculations directly through your AI client. This MCP gives your agent the specific chemical engineering logic needed to design BTX extraction processes. Instead of manually checking solubility data or sizing columns in separate spreadsheets, you can ask your agent to run the numbers for you. 

You start by checking if your feedstock is even worth processing. Once you know the composition is right, you can move on to selecting the best solvent for the job. The MCP handles the math for physical equipment, giving you the dimensions for columns or mixer-settlers based on your flow rates. Finally, you get a clear picture of your expected purity and recovery rates. It turns your AI client into a specialized process design assistant that understands liquid-liquid extraction and extractive distillation logic.

## Tools

### analyze_feedstock_suitability
This tool checks if your feedstock composition works with standard extraction methods. It also identifies the main separation hurdles you'll face.

### calculate_recovery_performance
Get your final numbers here. It predicts the specific purity and recovery percentage for your target product.

### design_extractor_dimensions
This tool calculates the physical size and capacity for your extraction unit. It works for both columns and mixer-settlers.

### select_optimal_solvent
Use this to find the best solvent candidate. It picks the right option based on your feedstock and the separation performance you need.

## Prompt Examples

**Prompt:** 
```
Is my feedstock suitable for extraction?
```

**Response:** 
```
The feedstock has an aromatic fraction of 0.4 and a non-aromatic concentration of 0.6, making it suitable for Liquid-Liquid Extraction (LLE) with medium process intensity.
```

**Prompt:** 
```
What is the best solvent for benzene extraction with a selectivity of 15?
```

**Response:** 
```
The recommended solvent is Sulfolane, which provides an estimated selectivity of 18.5 and high capacity for benzene.
```

**Prompt:** 
```
Calculate the column diameter for a 100 m3/h feed using Sulfolane.
```

**Response:** 
```
The calculated column diameter is 2.4 meters with a height of 12.5 meters for the specified flow rate and solvent ratio.
```

## Capabilities

### Feedstock Assessment
Your agent uses this to determine if a specific composition is compatible with extraction.

### Solvent Selection
The AI identifies the most effective chemical candidate for your specific separation goals.

### Equipment Sizing
Your agent calculates the physical dimensions and capacity for extraction columns or mixer-settlers.

### Yield Prediction
The AI calculates expected purity and recovery percentages for the final product.

## Use Cases

### Initial Feasibility Studies
Check if a new feedstock stream can be processed using standard LLE methods.

### Solvent Optimization
Compare different solvent candidates to find the best selectivity for benzene extraction.

### Equipment Specification
Generate the required height and diameter for an extraction column based on flow rates.

### Yield Forecasting
Estimate the final purity of aromatics to ensure they meet product specifications.

## Benefits

- Reduces manual calculation time for column sizing and capacity.
- Provides data-driven solvent selection based on feedstock type.
- Connects process design logic directly to your existing AI workflow.
- Predicts recovery performance before you commit to a design.

## How It Works

Connect the MCP to your AI client and start running chemical engineering calculations through natural language.

1. Connect your AI client to the Vinkius hosted MCP.
2. Provide feedstock or solvent requirements to your agent.
3. The agent calls the specific tool to run the math.
4. Receive technical dimensions, solvent recommendations, or yield predictions.

## Frequently Asked Questions

**What kind of extraction processes does this MCP support?**
It supports liquid-liquid extraction and extractive distillation logic for BTX processes.

**Can I use this to size a mixer-settler?**
Yes, the design_extractor_dimensions tool calculates the size and capacity for both columns and mixer-settlers.

**How does the solvent selection work?**
The select_optimal_solvent tool identifies the best chemical candidate by looking at your feedstock type and desired separation performance.

**Which AI clients can I use with this?**
You can use any MCP-compatible client like Claude, Cursor, Windsurf, or VS Code.

**Do I need to host the MCP myself?**
No, Vinkius hosts and manages the MCP for you. You just connect your client and start working.

**What is the difference between LLE and ED?**
Liquid-Liquid Extraction (LLE) uses solubility differences to separate aromatics, while Extractive Distillation (ED) uses a solvent to alter relative volatility in a distillation column.

**How do I determine the equipment size?**
You can use the `design_extractor_dimensions` tool by providing the selected solvent name, feed flow rate, and solvent-to-feed ratio.

**Can I predict product purity?**
Yes, the `calculate_recovery_performance` tool predicts aromatic recovery, product purity, and raffinate purity based on your design parameters.