# Crude Oil Assay Analysis AI Agent Connect

> Crude Oil Assay Analysis MCP gives your AI agent the mathematical tools needed for refinery planning and crude characterization. It handles everything from feedstock classification to yield distribution and blend compatibility checks, turning raw TBP data into actionable refinery insights.

## Overview
- **Category:** energy
- **Price:** Free
- **Endpoint:** https://edge.vinkius.com/vk_preview_CoyGGWc5M83g7xnPI80rFxFT1PKWRpvgaSRuD4mV/ai-agent-connect
- **Tags:** refinery, crude-oil, distillation, yield-analysis, blending

## Description

You can now bring heavy petroleum math into your AI workflow. This MCP gives your agent the ability to process crude oil data and predict how different feedstocks will behave in a refinery setting. Instead of manually calculating yields or checking blend specs, you can hand raw data to your AI client and let it run the numbers for you.

Whether you are working with TBP distillation data or trying to predict how a new crude will impact your product qualities, this MCP provides the specific tools to do it. You can categorize feedstock using get_crude_classification, estimate product volumes through calculate_yield_distribution, and predict refined properties with estimate_product_qualities. If you need to know if a specific mix of crudes will hit your target specs, evaluate_blend_compatibility handles the verification. It turns your AI from a simple text generator into a technical tool for refinery planning and crude characterization.

## Tools

### estimate_product_qualities
This tool predicts refined product properties. It uses crude characteristics to estimate things like sulfur content or viscosity.

### evaluate_blend_compatibility
This tool verifies if mixing different crude oils will meet your target specifications. It checks if the resulting blend stays within required limits.

### get_crude_classification
This tool categorizes crude oil feedstock. It uses API gravity and sulfur content to label crudes as light, heavy, sweet, or sour.

### calculate_yield_distribution
This tool calculates product volumes from TBP data. It uses distillation curves to estimate how much of each cut will be produced.

## Prompt Examples

**Prompt:** 
```
Classify a crude with 32 API gravity and 0.5% sulfur content.
```

**Response:** 
```
The crude is classified as Light/Sweet.
```

**Prompt:** 
```
What is the yield distribution for this TBP data: [{'temp': 100, 'vol': 10}, {'temp': 200, 'vol': 40}] with cuts [{'name': 'Naphtha', 'startTemp': 50, 'endTemp': 150}]?
```

**Response:** 
```
The Naphtha yield is 10%.
```

**Prompt:** 
```
Predict qualities for crude with 30 API, 2.0% sulfur, and 15 cSt viscosity.
```

**Response:** 
```
The estimated sulfur in distillates is 1.2% and the estimated viscosity index is 85.
```

## Capabilities

### Feedstock Classification
Your agent uses this to label crude types based on gravity and sulfur levels.

### Yield Estimation
The AI calculates expected product volumes from distillation data.

### Quality Prediction
Your agent predicts refined product properties from raw crude inputs.

### Blend Verification
The AI checks if a crude mixture meets specific target requirements.

## Use Cases

### Refinery Yield Modeling
Input TBP data to see how much naphtha or diesel a specific crude will produce.

### Crude Blending
Check if a new crude addition will push your blend outside of sulfur or viscosity limits.

### Feedstock Screening
Quickly categorize incoming crude shipments as light, heavy, sweet, or sour.

### Product Quality Forecasting
Predict the sulfur and viscosity of refined products before you even process the crude.

## Benefits

- Automates petroleum math within your existing AI chat interface.
- Reduces manual calculation errors in yield and quality estimation.
- Speeds up the crude blending verification process.
- Provides instant classification for new feedstock samples.

## How It Works

Connect your AI client to Vinkius and start running petroleum calculations immediately.

1. Connect your AI client to the Vinkius hosted MCP.
2. Provide your crude oil data or TBP curves to your AI agent.
3. Ask the agent to perform a specific calculation like yield or classification.
4. The agent uses the MCP tools to process the data and return the result.

## Frequently Asked Questions

**What AI clients can I use with this MCP?**
You can use any MCP-compatible client, including Claude, Cursor, Windsurf, and 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.

**Can this MCP handle TBP distillation data?**
Yes. You can provide TBP data to the calculate_yield_distribution tool to estimate product volumes.

**How does the tool classify crude oil?**
The get_crude_classification tool uses parameters like API gravity and sulfur content to categorize the feedstock.

**Can I use this to check if a blend is valid?**
Yes. The evaluate_blend_compatibility tool is designed to verify if a crude mix meets your target specifications.

**What can I calculate with this server?**
You can classify crude oil types, estimate product yields from distillation curves, predict product qualities, and check if crude blends meet specific targets.

**How do I provide TBP data?**
TBP data should be provided as a JSON string containing objects with temperature and cumulative volume percentage.

**Can I check if a blend is compatible?**
Yes, use the blend evaluation tool to determine if mixing two crudes will satisfy your target API, sulfur, or viscosity limits.