MCP For Claude Marketplace
Polymer Molecular Weight Distribution Modeling

Polymer Molecular Weight Distribution Modeling MCP Connector for Claude

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Simulate and analyze polymer molecular weight distributions using statistical models.

4 tools Official Updated Oct 1, 2026 Official Vinkius Partner
More Details Connect to Claude

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.

polymermolecular-weightstatisticschemistry-modelingpolydispersity

4 tools expose this connector's capabilities to your AI agent.

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

See how to talk to your AI agent using Polymer Molecular Weight Distribution Modeling.

Calculate the molecular weight moments for a Flory distribution with a scale parameter of 5000.

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

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

The parameters are valid for the Schulz-Zimm distribution.

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

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

The server supports Flory (Most Probable), Schulz-Zimm, and Log-Normal distributions via the `calculate_moments` tool.

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