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Skill v1.0.1
currentAutomated scan100/100internscience/scp/chemical-structure-comparison
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PublishedJune 16, 2026 at 01:28 AM
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version: "1.0.1" name: chemical_structure_comparison description: "Chemical Structure Comparison - Compare chemical structures: get SMILES, analyze structures, compute similarity, and check PubChem records. Use this skill for cheminformatics tasks involving NameToSMILES ChemicalStructureAnalyzer calculate smiles similarity get compound by name. Combines 4 tools from 4 SCP server(s)."
Chemical Structure Comparison
Discipline: Cheminformatics | Tools Used: 4 | Servers: 4
Description
Compare chemical structures: get SMILES, analyze structures, compute similarity, and check PubChem records.
Tools Used
- `NameToSMILES` from
server-31(sse) -https://scp.intern-ai.org.cn/api/v1/mcp/31/SciToolAgent-Chem - `ChemicalStructureAnalyzer` from
server-28(sse) -https://scp.intern-ai.org.cn/api/v1/mcp/28/InternAgent - `calculate_smiles_similarity` from
server-2(streamable-http) -https://scp.intern-ai.org.cn/api/v1/mcp/2/DrugSDA-Tool - `get_compound_by_name` from
pubchem-server(streamable-http) -https://scp.intern-ai.org.cn/api/v1/mcp/8/Origene-PubChem
Workflow
- Convert names to SMILES
- Analyze both structures
- Compute similarity
- Get PubChem compound data
Test Case
Input
json
{"compound_a": "aspirin","compound_b": "ibuprofen"}
Expected Steps
- Convert names to SMILES
- Analyze both structures
- Compute similarity
- Get PubChem compound data
Usage Example
Note: Replace<YOUR_SCP_HUB_API_KEY>with your own SCP Hub API Key. You can obtain one from the SCP Platform.
python
import asyncioimport jsonfrom mcp import ClientSessionfrom mcp.client.streamable_http import streamablehttp_clientfrom mcp.client.sse import sse_clientSERVERS = {"server-31": "https://scp.intern-ai.org.cn/api/v1/mcp/31/SciToolAgent-Chem","server-28": "https://scp.intern-ai.org.cn/api/v1/mcp/28/InternAgent","server-2": "https://scp.intern-ai.org.cn/api/v1/mcp/2/DrugSDA-Tool","pubchem-server": "https://scp.intern-ai.org.cn/api/v1/mcp/8/Origene-PubChem"}async def connect(url, transport_type):transport = streamablehttp_client(url=url, headers={"SCP-HUB-API-KEY": "<YOUR_SCP_HUB_API_KEY>"})read, write, _ = await transport.__aenter__()ctx = ClientSession(read, write)session = await ctx.__aenter__()await session.initialize()return session, ctx, transportdef parse(result):try:if hasattr(result, 'content') and result.content:c = result.content[0]if hasattr(c, 'text'):try: return json.loads(c.text)except: return c.textreturn str(result)except: return str(result)async def main():# Connect to required serverssessions = {}sessions["server-31"], _, _ = await connect("https://scp.intern-ai.org.cn/api/v1/mcp/31/SciToolAgent-Chem", "sse")sessions["server-28"], _, _ = await connect("https://scp.intern-ai.org.cn/api/v1/mcp/28/InternAgent", "sse")sessions["server-2"], _, _ = await connect("https://scp.intern-ai.org.cn/api/v1/mcp/2/DrugSDA-Tool", "streamable-http")sessions["pubchem-server"], _, _ = await connect("https://scp.intern-ai.org.cn/api/v1/mcp/8/Origene-PubChem", "streamable-http")# Execute workflow steps# Step 1: Convert names to SMILESresult_1 = await sessions["server-31"].call_tool("NameToSMILES", arguments={})data_1 = parse(result_1)print(f"Step 1 result: {json.dumps(data_1, indent=2, ensure_ascii=False)[:500]}")# Step 2: Analyze both structuresresult_2 = await sessions["server-28"].call_tool("ChemicalStructureAnalyzer", arguments={})data_2 = parse(result_2)print(f"Step 2 result: {json.dumps(data_2, indent=2, ensure_ascii=False)[:500]}")# Step 3: Compute similarityresult_3 = await sessions["server-2"].call_tool("calculate_smiles_similarity", arguments={})data_3 = parse(result_3)print(f"Step 3 result: {json.dumps(data_3, indent=2, ensure_ascii=False)[:500]}")# Step 4: Get PubChem compound dataresult_4 = await sessions["pubchem-server"].call_tool("get_compound_by_name", arguments={})data_4 = parse(result_4)print(f"Step 4 result: {json.dumps(data_4, indent=2, ensure_ascii=False)[:500]}")# Cleanupprint("Workflow complete!")if __name__ == "__main__":asyncio.run(main())