# Catalyst Lifetime Prediction AI Agent Connect

> Catalyst Lifetime Prediction MCP gives your AI client the ability to model catalyst deactivation and operational lifespans. Use it to calculate remaining life, determine the best time for regeneration, and simulate how changes in feed or temperature impact your catalyst's health through coking and metal poisoning analysis.

## Overview
- **Category:** analytics
- **Price:** Free
- **Endpoint:** https://edge.vinkius.com/vk_preview_093P8yd7E4Kt1tw3yPZSMFTBPfjYygVvGwe9OHZr/ai-agent-connect
- **Tags:** catalyst, refinery, kinetics, maintenance, prediction

## Description

You can use this MCP to bring chemical kinetics and refinery operational data directly into your AI workflow. Instead of manually calculating deactivation rates, you let your agent handle the heavy lifting. It analyzes coking, metal poisoning, and specific operating conditions to give you a clear picture of your catalyst's status. 

You can run simulations to see how a change in feed temperature or process conditions will accelerate deactivation before you actually make the change in the field. It helps you move away from guesswork by providing specific windows for regeneration and clear urgency levels for replacement. Whether you are trying to optimize a maintenance schedule or assess the risk of a new operating parameter, this MCP provides the mathematical backbone for your decisions.

## Tools

### get_replacement_urgency
This tool determines how soon you need to replace a catalyst. It analyzes current operating conditions and poisoning levels to set an urgency level.

### predict_remaining_life
This tool calculates the expected operational lifespan left for your catalyst. It uses current deactivation data to project future performance.

### simulate_deactivation_scenario
This tool models the impact of changing process or feed conditions. It shows how shifts in temperature or feed composition affect deactivation rates.

### calculate_regeneration_window
This tool identifies the best time to perform catalyst regeneration. It finds the optimal window to restore activity without unnecessary downtime.

## Prompt Examples

**Prompt:** 
```
How many days of operational life are left for our catalyst?
```

**Response:** 
```
There are 45 days of operational life remaining before the catalyst must be replaced.
```

**Prompt:** 
```
What happens if we increase the feed temperature by 10 degrees?
```

**Response:** 
```
Increasing the temperature will accelerate coking, reducing the projected remaining life by 12 days.
```

**Prompt:** 
```
Is it urgent to replace the catalyst now?
```

**Response:** 
```
The urgency level is High. You have 5 days until the activity reaches the critical threshold.
```

## Capabilities

### Deactivation Modeling
Your agent uses this to project how quickly a catalyst loses activity over time.

### Maintenance Planning
The AI identifies the best time for regeneration to minimize production impact.

### Risk Assessment
Your client evaluates the urgency of replacement based on coking and metal poisoning.

### Process Simulation
The agent tests how new operating conditions will change the catalyst's lifespan.

## Use Cases

### Optimizing Regeneration
Find the exact window to regenerate a catalyst to maximize uptime.

### Feed Change Impact Analysis
Simulate how a new feed composition will accelerate coking or poisoning.

### Shutdown Planning
Determine if a catalyst needs replacement during the next scheduled turnaround.

### Operational Risk Management
Monitor real-time deactivation kinetics to assess the risk of running a catalyst too long.

## Benefits

- Reduces guesswork in maintenance scheduling by providing specific regeneration windows.
- Prevents unplanned downtime by predicting replacement urgency before failure.
- Quantifies the impact of process changes on catalyst lifespan through simulation.

## How It Works

Connect your AI client to Vinkius to start running refinery analytics immediately.

1. Connect your preferred MCP-compatible client like Claude or Cursor to Vinkius.
2. Provide your current catalyst operating data to your agent.
3. Ask your agent to run a simulation or a life prediction.
4. Receive specific, actionable data on remaining life or replacement urgency.

## Frequently Asked Questions

**How does this MCP predict catalyst life?**
It uses deactivation kinetics, including coking and metal poisoning data, to model the remaining operational lifespan.

**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 happens if I change my feed temperature?**
You can use the simulation tool to see exactly how much that temperature change will accelerate deactivation and reduce remaining life.

**How do I know when to replace a catalyst?**
The tool provides a replacement urgency level based on current activity and operating conditions.

**Do I need to host the MCP myself?**
No, Vinkius hosts and manages the MCP for you, so it is ready to use as soon as you connect your client.