mcpField
M
Molecule Visualizer MCP Server

Molecule Visualizer MCP Server

Local
github.com/leelasdScience & Education2Updated 76w ago

About Molecule Visualizer MCP Server

An MCP server for chemistry workflows, aimed at LLM applications such as Claude Desktop. It turns molecule names or SMILES strings into 2D images and reports molecular properties, with a database of common molecules.

Key features

  1. 012D molecule images from names or SMILES
  2. 02Molecular formula, weight, atom and bond counts
  3. 03Lipinski properties, including LogP
  4. 04Common-molecule lookup and SMILES resources
  5. 05Optional atom indices and image dimensions

Use cases

  1. 01Viewing a molecule structure in Claude Desktop
  2. 02Checking basic properties of a molecule
  3. 03Preparing molecule diagrams for educational content
  4. 04Looking up SMILES for a common molecule

MCP support

Exposes visualization and property tools, plus resources for common molecules, to MCP clients. Visualizations can be returned as MCP Image objects or as Markdown with an embedded image.

Configuration

Local server config is the same for every client. Copy it into your client’s MCP config file.

No install method listed yet

We haven’t collected a package or remote endpoint for this server. Follow the instructions in the project README.

Repository

Tools

No tool list yet

Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.

Details

From the project README

Molecule Visualizer MCP Server

Molecule Visualizer Python RDKit License

A Model Context Protocol (MCP) server that provides tools for visualizing molecules and retrieving molecular properties using SMILES codes. This server integrates with LLM applications like Claude Desktop to provide chemistry-focused capabilities.

Table of Contents

Overview

The Molecule Visualizer MCP server provides LLM applications with the ability to:

  1. Generate 2D visualizations of molecules from SMILES strings
  2. Calculate and display molecular properties
  3. Access a database of common molecules by name

This enables chemistry-related use cases such as exploring molecular structures, analyzing chemical properties, and generating molecule visualizations for educational content or research assistance.

Screenshots

Using the MCP Server with Claude

MCP in Claude

Claude using the Molecule Visualizer MCP server to display molecular structures.

Visualizing Molecules using SMILES

Visualizing with SMILES

Providing direct SMILES codes to generate molecular visualizations.

Comparison with Web Access

Claude with Web Access

Attempting similar visualization with web access did not work as Claude fails at getting the right smiles code from the internet. - MCP provides more reliable chemistry capabilities if pubchempy and chembl client are added to this.

Features

Molecule Visualization
  • Generate 2D visualizations of molecules from SMILES strings or common names
  • Returns proper MCP Image objects for direct integration with LLM applications
  • Option for markdown-compatible version with base64-encoded images
  • Customizable image dimensions and display options
  • Option to show atom indices for educational purposes
Molecular Properties
  • Basic properties:
    • Molecular formula
    • Molecular weight
    • Atom and bond counts
    • Ring count
  • Lipinski's Rule of Five properties:
    • Hydrogen bond donors
    • Hydrogen bond acceptors
    • Rotatable bonds
    • LogP (lipophilicity)

Installation

Prerequisites
  • Python 3.10 or higher
  • RDKit (cheminformatics library)
  • MCP Python SDK
  • PIL (Python Imaging Library)
Step-by-step Installation
  1. Clone this repository:

    git clone https://github.com/yourusername/molecule-visualizer.git
    cd molecule-visualizer
    
  2. Run the setup script which creates a virtual environment and installs dependencies:

    chmod +x setup.sh
    ./setup.sh
    
  3. Activate the virtual environment:

    source venv/bin/activate
    
Alternative Installation using uv

You can also use the fast uv package manager (recommended in the MCP documentation):

  1. Install uv if you don't already have it:

    pip install uv
    
  2. Create a virtual environment:

    uv venv
    
  3. Install dependencies:

    uv pip install -r requirements.txt
    

    Or install dependencies directly:

    uv add "mcp[cli]"
    uv add "rdkit>=2023.3.1"
    uv add "pillow>=10.0.0"
    
  4. Activate the virtual environment:

    source .venv/bin/activate
    

Usage

Running the Server

To run the server directly:

python molecule_server.py

The server will start and listen for MCP connections.

With Claude Desktop
  1. Install Claude Desktop

  2. Edit your Claude Desktop configuration file:

    • macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
    • Windows: %APPDATA%\Claude\claude_desktop_config.json
  3. Add the Molecule Visualizer server configuration:

{
  "mcpServers": {
    "Molecule Visualizer": {
      "command": "uv",
      "args": [
        "run",
        "--with",
        "mcp[cli]",
        "--with",
        "pillow",
        "--with",
        "rdkit",
        "mcp",
        "run",
        "/ABSOLUTE-PATH-TO-MOLECULE-SERVER/molecule_server.py"
      ]
    }
  }
}
  1. Restart Claude Desktop

  2. In Claude, you can now use molecule visualization:

    Please show me a visualization of aspirin
    
Test Client

A test client is included to demonstrate how to use the server:

python test_client.py

This will connect to the server and run through several examples of using the tools and resources.

API Reference

Tools
visualize_molecule

Generate a 2D visualization of a molecule as an Image object.

Parameters:

  • query (string): Molecule name or SMILES string
  • width (integer, optional): Width in pixels (default: 400)
  • height (integer, optional): Height in pixels (default: 300)
  • show_atom_indices (boolean, optional): Whether to show atom indices (default: false)

Returns:

  • Image object containing the molecule visualization (PNG format)
visualize_molecule_markdown

Generate a 2D visualization of a molecule as a markdown string with embedded base64-encoded image.

Parameters:

  • Same as visualize_molecule

Returns:

  • Markdown string with embedded base64-encoded PNG image
get_molecule_properties

Get properties of a molecule.

Parameters:

  • query (string): Molecule name or SMILES string

Returns:

  • Markdown formatted text with molecular properties
get_common_molecules

Get a list of common molecules that can be visualized.

Parameters:

  • None

Returns:

  • Markdown formatted list of common molecule names
Resources
molecule://{name}/smiles

Get the SMILES string for a common molecule.

Parameters:

  • name (string): Name of the common molecule

Returns:

  • SMILES string for the molecule
molecules://common

List all common molecules available in the database.

Returns:

  • JSON formatted list of molecule names and their SMILES strings

Examples

Visualizing a Molecule
from mcp import ClientSession, StdioServerParameters
from mcp.client.stdio import stdio_client

async def visualize():
    server_params = StdioServerParameters(
        command="python",
        args=["path/to/molecule_server.py"],
        env=None
    )
    
    async with stdio_client(server_params) as (stdin, stdout):
        client = ClientSession(stdin, stdout)
        await client.initialize()
        
        # Visualize aspirin
        result = await client.call_tool("visualize_molecule", {"query": "aspirin"})
        
        # The image data is in result.content[0].image.data
        # The image format is in result.content[0].image.format
        
        # Save the image to a file
        with open("aspirin.png", "wb") as f:
            f.write(result.content[0].image.data)
Getting Molecule Properties
# Using the client from above
result = await client.call_tool("get_molecule_properties", {"query": "caffeine"})
print(result.content[0].text)

Requirements

Dependencies are listed in requirements.txt:

mcp[cli]>=0.1.0
rdkit>=2023.3.1
pillow>=10.0.0

License

This project is licensed under the Apache License - see the LICENSE file for details.

Contributing

Contributions are welcome! Here are ways you can contribute:

  1. Add new molecular visualization options
  2. Expand the common molecules database
  3. Add additional molecular properties calculations
  4. Improve error handling and documentation
  5. Create additional examples

To contribute:

  1. Fork the repository
  2. Create a feature branch
  3. Make your changes
  4. Submit a pull request

Please ensure your code follows the existing style and includes appropriate tests and documentation.

Comments

Markdown supported

New to MCP?

From what the protocol is to installing your first server, these answers cover most first questions.

An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.