# Fluid Catalytic Cracking Design Suite AI Agent Connect

> Fluid Catalytic Cracking (FCC) Design Suite gives your AI client the engineering logic needed to design and optimize FCC units. It handles the heavy lifting of calculating product yields, managing catalyst circulation, and predicting the thermal environment of the regenerator. You can use it to assess catalyst health and maintain precise heat balances during heavy oil conversion.

## Overview
- **Category:** engineering
- **Price:** Free
- **Endpoint:** https://edge.vinkius.com/vk_preview_hYQA2nOemqhUFvtL5uef7tIHuLk8125ZHX0ZuiL2/ai-agent-connect
- **Tags:** fcc, refinery, hydrocarbons, catalysis, chemical-engineering

## Description

You can now run complex FCC unit design calculations directly through your AI client. This MCP provides the specific engineering tools required to model how heavy hydrocarbons convert into high-value products like gasoline and olefins. Instead of manually calculating mass flows or thermal profiles, you tell your agent what your feed properties and conversion targets are, and it handles the math.

When you're designing a unit, you can use this MCP to determine how much catalyst needs to circulate to keep the heat balance stable. It also lets you look ahead at the regenerator's thermal and chemical environment to avoid operational issues. If you're worried about feed contaminants or temperature spikes, the suite can assess deactivation risks to help you understand how quickly your catalyst might lose effectiveness. It turns your AI into a specialized refinery engineering assistant that understands the relationship between feed density, CCR, and final product distribution.

## Tools

### analyze_deactivation_risk
This tool assesses how quickly your catalyst will lose its effectiveness based on operating conditions.

### calculate_product_yields
This tool determines the expected volume distribution of products based on your specific feed and catalyst inputs.

### determine_catalyst_circulation
Use this to calculate the required mass flow of catalyst needed to maintain both the reaction and heat balance.

### evaluate_regenerator_conditions
This tool predicts the thermal and chemical environment inside the regenerator.

## Prompt Examples

**Prompt:** 
```
Calculate the product yields for a VGO feed with density 0.85, CCR of 0.5, and distillation endpoint of 550, targeting 70% conversion with a catalyst activity of 0.9.
```

**Response:** 
```
The predicted yields are: Gasoline 52.5%, LCO 18.2%, HCO 10.3%, Coke 8.5%, and Gas 10.5%.
```

**Prompt:** 
```
What is the required catalyst circulation rate for a feed flow of 50,000 kg/h with a coke yield of 0.08 and a heat requirement of 1,200,000 kJ/h?
```

**Response:** 
```
The required catalyst mass flow rate is 15,000 kg/h, resulting in a circulation ratio of 0.3.
```

**Prompt:** 
```
Predict the regenerator conditions for a catalyst flow of 15,000 kg/h, a coke yield of 0.08, and an oxygen availability of 2.0.
```

**Response:** 
```
The predicted regenerator temperature is 695°C, with a flue gas composition of 3% CO and 2% O2.
```

## Capabilities

### Yield Prediction
Your agent calculates volume distributions for gasoline, olefins, and other products.

### Heat Balance Management
The AI determines the necessary catalyst mass flow to keep the reactor stable.

### Regenerator Modeling
Your client predicts the thermal and chemical state of the regenerator environment.

### Catalyst Health Assessment
The MCP evaluates how feed contaminants and temperature affect catalyst life.

## Use Cases

### Unit Design Iteration
Run multiple scenarios to find the optimal catalyst circulation for a new FCC unit design.

### Feedstock Change Analysis
Check how switching to a different VGO feed affects your gasoline and olefin yields.

### Operational Safety
Predict regenerator temperatures to ensure they stay within safe operating limits.

### Catalyst Lifecycle Planning
Evaluate how temperature and contaminants will impact how fast you need to replace catalyst.

## Benefits

- Calculates product distributions based on feed density and CCR.
- Maintains heat balance by determining precise catalyst circulation rates.
- Predicts regenerator thermal environments to prevent operational upsets.
- Assesses catalyst deactivation risks from feed contaminants.

## How It Works

Connect your AI client to Vinkius to access these engineering tools instantly.

1. Connect your MCP-compatible client like Claude or Cursor to Vinkius.
2. Provide your feed properties and target conversion to your AI agent.
3. The agent calls the specific FCC design tool needed for the calculation.
4. The MCP returns the calculated yields, flow rates, or thermal conditions.
5. Your agent presents the technical results for your review.

## Frequently Asked Questions

**What kind of feedstocks can this MCP model?**
The tools are designed to model heavy hydrocarbons, such as VGO, for conversion in FCC units.

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

**Does this MCP handle heat balance calculations?**
Yes, the determine_catalyst_circulation tool calculates the mass flow required to maintain the heat balance.

**How does the MCP help with catalyst management?**
It uses the analyze_deactivation_risk tool to assess how quickly catalyst effectiveness drops based on temperature and contaminants.

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

**How do I calculate the expected gasoline yield?**
You can use the `calculate_product_yields` tool. Provide the feed properties (density, CCR, and distillation endpoint), the desired conversion target, and the catalyst activity level.

**Can this tool help with heat balance calculations?**
Yes. Use `determine_catalyst_circulation` to calculate the necessary mass flow of catalyst required to satisfy the endothermic heat requirement of the cracking reaction.

**How is catalyst deactivation assessed?**
The `analyze_deactivation_risk` tool assesses risk by evaluating the feed type (VGO or Residue), metal content, and the predicted regenerator temperature.