Version: 0.1.0
Last Update: 2025/06/05
MCP Support
Python Calling Support
Identify functional groups in a molecule.
Example
Input:
smiles: 'CCO'
Text Input (used for the run_text
function in the Python calling mode):
smiles: 'CCO'
Output:
'This molecule contains alcohol groups, and side-chain hydroxyls.'
Usage
The tool supports both MCP mode and Python calling mode.
MCP Mode
Configure your MCP client following its instructions with something like:
{
"command": "/ABSTRACT/PATH/TO/uv", // Use `which uv` to get its path
"args": ["--directory", "/ABSTRACT/PATH/TO/ChemMCP", "run", "--tools", "FunctionalGroups"],
"toolCallTimeoutMillis": 300000,
"env": {}
}
Python Calling Mode
import os
from chemmcp.tools import FunctionalGroups
# Initialize the tool
tool = FunctionalGroups()
# The tool has two alternative ways to run:
# 1. Run with separate input domains (recommended)
output = tool.run_code(
smiles='CCO'
)
# 2. Run with text-only input
output = tool.run_text(
smiles='CCO'
)
Each tool in ChemMCP has two ways to run:
run_code
(recommended): The inputs contain one or more domains, each of which can be a str, an int, a float, etc.run_text
: The inputs are a single string in a specific format. The tool will parse the string to extract the input domains. This is useful in scenarios where an agent framework calls tools only with text input. The output is the same in both cases.
For the input and output domains, please refer to the tool’s signature.
Tool Signature
Input
Used in the MCP mode, as well as the run_code
function in the Python calling mode.
Name | Type | Default | Description |
---|---|---|---|
smiles | str | N/A | SMILES string of the molecule. |
Text Input
Used in the run_text
function in the Python calling mode.
Name | Type | Default | Description |
---|---|---|---|
smiles | str | N/A | SMILES string of the molecule. |
Output
The output is the same in both input cases.
Name | Type | Description |
---|---|---|
fgs | str | A description of functional groups in the molecule. |
Envs
No required environment variables for this tool.
Implementation Details
- Implementation Description: Uses RDKit’s SMARTS patterns to identify functional groups in a molecule. The tool checks for a comprehensive list of common functional groups including alcohols, aldehydes, ketones, carboxylic acids, and many others.
- Open-source dependencies (code source or required libraries):
- ChemCrow (MIT)
- Hosted services and software (required for running the tool): None