Paramus MCP Server

Model Context Protocol Tools for Chemistry, Math & Data Science

Overview

The Paramus MCP Server provides 46 specialized tools accessible through VS Code Copilot via the Model Context Protocol. All tools are tested and validated with real outputs.

20

Chemistry Tools

8

Polymer Tools

4

Math Tools

14

Data Science & Python

Tool Navigation Tree

Professional jsTree component - click to expand/collapse, search tools

Chemistry Tools (RDKit)

Molecular analysis and cheminformatics powered by RDKit

calculate_molecular_weight

Calculate molecular weight from SMILES

@paramus calculate molecular weight of c1ccccc1
Core

calculate_logp

Calculate LogP (lipophilicity)

@paramus calculate LogP for aspirin CC(=O)Oc1ccccc1C(=O)O
Property

check_lipinski_ro5

Check drug-likeness (Lipinski's Rule of Five)

@paramus check Lipinski's rule of five for caffeine CN1C=NC2=C1C(=O)N(C(=O)N2C)C
Drug Design

smiles_to_inchi

Convert SMILES to InChI format

@paramus convert SMILES CCO to InChI
Conversion

inchi_to_smiles

Convert InChI to SMILES format

@paramus convert InChI=1S/C2H6O/c1-2-3/h3H,2H2,1H3 to SMILES
Conversion

mol_to_canonical_smiles

Generate canonical SMILES

@paramus canonicalize SMILES C(C)O
Conversion

calculate_tpsa

Calculate Topological Polar Surface Area

@paramus calculate TPSA for ibuprofen CC(C)Cc1ccc(cc1)C(C)C(=O)O
Property

count_hbd

Count hydrogen bond donors

@paramus count H-bond donors in glucose OC[C@H]1OC(O)[C@H](O)[C@@H](O)[C@@H]1O
Property

count_hba

Count hydrogen bond acceptors

@paramus count H-bond acceptors in acetone CC(=O)C
Property

count_rotatable_bonds

Count rotatable bonds

@paramus count rotatable bonds in n-butane CCCC
Property

count_rings

Count all rings in molecule

@paramus count rings in naphthalene c1ccc2ccccc2c1
Structure

count_aromatic_rings

Count aromatic rings

@paramus count aromatic rings in biphenyl c1ccc(cc1)c2ccccc2
Structure

count_chiral_centers

Count chiral centers

@paramus count chiral centers in menthol CC(C)[C@@H]1CC[C@@H](C)C[C@H]1O
Structure

get_molecular_formula

Get molecular formula

@paramus get molecular formula for ethanol CCO
Core

smiles_to_mol

Parse SMILES and get basic info

@paramus parse SMILES c1ccccc1 and get molecule info
Core

calculate_similarity

Calculate Tanimoto similarity

@paramus calculate similarity between CCO and CCCO
Analysis

add_hydrogens

Add explicit hydrogens

@paramus add explicit hydrogens to CCO
Modification

remove_hydrogens

Remove explicit hydrogens

@paramus remove explicit hydrogens from [H]C([H])([H])O[H]
Modification

generate_3d_coords

Generate 3D coordinates

@paramus generate 3D coordinates for benzene c1ccccc1
3D

sanitize_molecule

Sanitize molecule structure

@paramus sanitize molecule CCO
Validation

Polymer Tools (pSMILES)

Polymer structure analysis and manipulation using polymer SMILES notation

is_psmiles

Validate polymer SMILES notation

@paramus check if *CC* is valid pSMILES
Validation

canonicalize_psmiles

Canonicalize polymer SMILES to standard form

@paramus canonicalize polymer SMILES *CC(C)*
Core

get_polymer_fingerprint

Generate molecular fingerprint for polymers

@paramus get polymer fingerprint for *CC*
Analysis

dimerize_psmiles

Create dimer from monomer unit

@paramus create dimer from monomer *CC*
Synthesis

create_alternating_copolymer

Create alternating copolymer structure

@paramus create alternating copolymer from *CC* and *C(C)C*
Synthesis

randomize_psmiles

Generate random structural variations

@paramus generate 5 random variations of *CC*
Generation

compute_polymer_similarity

Calculate similarity between polymers

@paramus compare polymer similarity between *CC* and *C(C)C*
Comparison

Math Tools

Basic mathematical operations

double_number

Double a number

@paramus double the number 42
Arithmetic

square_number

Square a number

@paramus square the number 7
Arithmetic

add_numbers

Add two numbers

@paramus add 15 and 27
Arithmetic

multiply_numbers

Multiply two numbers

@paramus multiply 12 by 8
Arithmetic

Data Science Tools

Experimental design (DOE) and machine learning

Experimental Design (7 tools)

full_factorial

Full factorial design

@paramus create full factorial design with 3 factors at 2 levels
DOE

fractional_factorial_2level

2-level factorial design

@paramus create 2-level fractional factorial for 4 factors
DOE

fractional_factorial

Fractional factorial design

@paramus generate fractional factorial design with generator a b ab
DOE

plackett_burman

Plackett-Burman design

@paramus create Plackett-Burman design for 7 factors
DOE

box_behnken

Box-Behnken design

@paramus generate Box-Behnken design with 3 factors
DOE

central_composite

Central Composite design

@paramus create central composite design for 4 factors
DOE

latin_hypercube

Latin Hypercube Sampling

@paramus generate 50 samples using Latin Hypercube for 3 dimensions
DOE

Machine Learning (5 tools)

train_random_forest_regressor

Train Random Forest model

@paramus train Random Forest with 100 trees on my data
ML

train_svr

Train Support Vector Regressor

@paramus train SVR model with RBF kernel
ML

train_linear_regression

Train Linear Regression

@paramus train linear regression model on dataset
ML

calculate_regression_metrics

Calculate MSE, RMSE, R²

@paramus calculate regression metrics for predictions vs actual
ML

split_train_test

Split data for training/testing

@paramus split dataset into 80% train and 20% test
ML

Setup & Installation

🌐 Official Download Portal

Get the latest version of Paramus MCP Server

Download from portal.paramus.ai →

Usage in VS Code

After installation, restart VS Code and use tools through Copilot:

@paramus calculate the molecular weight of benzene (c1ccccc1)
@paramus double the number 42
@paramus generate a Box-Behnken design with 3 factors
@paramus execute this Python: import numpy as np; print(np.mean([1,2,3,4,5]))

Supported Platforms

Requirements