About
RDKit Chemical Informatics Server integrates the RDKit open-source cheminformatics library with the Model Context Protocol to enable molecular analysis and computational chemistry capabilities within AI coding assistants. Key features include: - Molecular visualization: Generate 2D chemical structure images from SMILES strings and other molecular formats - Descriptor calculation: Compute molecular properties including molecular weight, logP, topological polar surface area (TPSA), and drug-likeness metrics - Cheminformatics operations: Perform molecular validation, substructure analysis, and chemical data processing tasks - Base64 image encoding: Convert molecular visualizations to base64 format for inline display
README
[](https://mseep.ai/app/s20ss-mcp-rdkit)
MCP RDKit Project
Overview
The mcp_rdkit project integrates the RDKit library with the MCP (Model Context Protocol) framework to provide advanced chemical informatics tools. It includes functionalities for molecular visualization, descriptor calculation, and interaction with an MCP server.
Features
Project Structure
mcp_rdkit/__main__.py: Entry point for the application. It initializes the MCP server and runs it in "stdio" mode.
- rdkit_helper.py: Contains helper functions for RDKit operations, including:
- Converting PIL images to base64.
- Interfacing with the MCP server.
- Utilizing RDKit for chemical computations.setup.py: Configuration for packaging and distribution.Requirements
Installation
1. Install the package using pip:
pip install mcp-rdkit
2. Run the application:
python -m mcp_rdkit
Demo
You can integrate this directly into Claude App:
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Usage
MCP Configuration Example
To use the RDKit server with MCP, add the following configuration to your mcp config file:
"rdkit-server": {
"type": "stdio",
"command": "python",
"args": [
"-m",
"mcp_rdkit"
]
}
RDKIT MCP is certified and indexed by MCP Review
[](https://mseep.ai/app/e504ca84-1db0-4bb5-be6d-1a20e0d96293)
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