Compound Name Retrieval

Compound Name to SMILES Retrieval

Usage

1. MCP Server Definition

import asyncio
import json
from contextlib import AsyncExitStack
from mcp.client.streamable_http import streamablehttp_client
from mcp import ClientSession

class DrugSDAClient:
    """DrugSDA-Tool MCP Client"""

    def __init__(self, server_url: str, api_key: str):
        self.server_url = server_url
        self.api_key = api_key
        self.session = None

    async def connect(self):
        """Establish connection and initialize session"""
        try:
            self.transport = streamablehttp_client(
                url=self.server_url,
                headers={"SCP-HUB-API-KEY": self.api_key}
            )
            self._stack = AsyncExitStack()
            await self._stack.__aenter__()
            self.read, self.write, self.get_session_id = await self._stack.enter_async_context(self.transport)
            self.session_ctx = ClientSession(self.read, self.write)
            self.session = await self._stack.enter_async_context(self.session_ctx)
            await self.session.initialize()
            return True
        except Exception as e:
            print(f"✗ connect failure: {e}")
            return False

    async def disconnect(self):
        """Disconnect from server"""
        try:
            if hasattr(self, '_stack'):
                await self._stack.aclose()
            print("✓ already disconnect")
        except Exception as e:
            print(f"✗ disconnect error: {e}")
    def parse_result(self, result):
        """Parse MCP tool call result"""
        try:
            if hasattr(result, 'content') and result.content:
                content = result.content[0]
                if hasattr(content, 'text'):
                    return json.loads(content.text)
            return str(result)
        except Exception as e:
            return {"error": f"parse error: {e}", "raw": str(result)}

2. Compound Name Retrieval Workflow

This workflow retrieves SMILES strings from PubChem using common chemical names.

Workflow Steps:

1. Input Compound Names - Provide list of chemical names
2. Query PubChem - Search for each compound in PubChem database
3. Extract SMILES - Retrieve canonical SMILES representations

Implementation:

## Initialize client
client = DrugSDAClient(
    "https://scp.intern-ai.org.cn/api/v1/mcp/2/DrugSDA-Tool",
    "<your-api-key>"
)

if not await client.connect():
    print("connection failed")
    exit()

## Input: List of compound names
compound_names = ["aspirin", "caffeine", "ibuprofen"]

## Retrieve SMILES from compound names
result = await client.session.call_tool(
    "retrieve_smiles_from_name",
    arguments={
        "compound_names": compound_names
    }
)

result_data = client.parse_result(result)
smiles_list = result_data["retrieve_smiles"]

## Display results
print("Retrieved SMILES strings:")
for item in smiles_list:
    print(f"Name: {item['compound_name']}")
    print(f"SMILES: {item['smiles']}\n")

await client.disconnect()

Tool Descriptions

DrugSDA-Tool Server:

• retrieve_smiles_from_name: Retrieve SMILES from PubChem by compound name
  • Args:
    • compound_names (list): List of chemical compound names
  • Returns:
    • retrieve_smiles (list): List of name-SMILES pairs
      • compound_name (str): Input compound name
      • smiles (str): Canonical SMILES string

Input/Output

Input:

• compound_names: List of chemical names (common names, IUPAC names, or synonyms)

Output:

• List of results:
  • compound_name: Query compound name
  • smiles: Canonical SMILES representation

Use Cases

• Convert chemical names to machine-readable formats
• Batch retrieve molecular structures
• Validate compound names against PubChem
• Prepare datasets for computational chemistry
• Integration with molecular analysis pipelines

Performance Notes

• Data source: PubChem public database
• Name matching: Supports common names, IUPAC names, and synonyms
• Execution time: ~1-2 seconds per compound
• Availability: Requires internet connection to PubChem API