# Polymer Molecular Weight Distribution Modeling AI Agent Connect

> Simulate and analyze polymer molecular weight distributions using statistical models.

## Overview
- **Category:** science
- **Price:** Free
- **Endpoint:** https://edge.vinkius.com/vk_preview_xFbNk2WUJzB7T8ym1DgbxEdRuT9aWFCGbh6OGLJl/ai-agent-connect
- **Tags:** polymer, molecular-weight, statistics, chemistry-modeling, polydispersity

## Description

This MCP server provides computational tools to model the molecular weight distribution of polymers. It allows users to calculate key macromolecular descriptors like Mn, Mw, Mz, and PDI using statistical models such as Flory, Schulz-Zimm, and Log-Normal. Users can also generate distribution curves and compare different distribution models to analyze polymer polydispersity.

## Tools

### compare_distributions
Compares two different distribution models

### generate_distribution_curve
Generates a set of data points representing the probability density or mass fraction

### validate_polymer_parameters
Checks if provided polymer parameters are physically realistic

### calculate_moments
Calculates fundamental molecular weight averages and PDI for a given distribution

## Prompt Examples

**Prompt:** 
```
Calculate the molecular weight moments for a Flory distribution with a scale parameter of 5000.
```

**Response:** 
```
The calculated moments for the Flory distribution are: Mn = 5000, Mw = 10000, Mz = 15000, and PDI = 2.0.
```

**Prompt:** 
```
Check if these parameters are valid for a Schulz-Zimm distribution: type='schulz_zimm', parameters='{"scale": 1000, "dispersion": 0.5}'
```

**Response:** 
```
The parameters are valid for the Schulz-Zimm distribution.
```

**Prompt:** 
```
Compare a Flory distribution (scale 4000) with a Log-Normal distribution (scale 4000, shape 1.5).
```

**Response:** 
```
The differences between the models are: deltaMn = 120.5, deltaMw = 450.2, deltaMz = 1100.8, and deltaPDI = 0.15.
```

## Frequently Asked Questions

**What statistical models are supported?**
The server supports Flory (Most Probable), Schulz-Zimm, and Log-Normal distributions via the `calculate_moments` tool.

**How can I visualize the distribution?**
You can use the `generate_distribution_curve` tool to obtain data points for the probability density across a specified weight range.

**Can I validate my parameters before running calculations?**
Yes, use the `validate_polymer_parameters` tool to ensure your distribution type and parameters are physically realistic.