molecular_visualization_suite
community[skill]
Molecular Visualization Suite - Visualize molecules: convert SMILES to formats, visualize molecule, visualize protein, visualize complex. Use this skill for chemical visualization tasks involving convert smiles to format visualize molecule visualize protein visualize complex. Combines 4 tools from 1 SCP server(s).
$
/plugin install InnoClawdetails
Molecular Visualization Suite
Discipline: Chemical Visualization | Tools Used: 4 | Servers: 1
Description
Visualize molecules: convert SMILES to formats, visualize molecule, visualize protein, visualize complex.
Tools Used
convert_smiles_to_formatfromserver-2(streamable-http) -https://scp.intern-ai.org.cn/api/v1/mcp/2/DrugSDA-Toolvisualize_moleculefromserver-2(streamable-http) -https://scp.intern-ai.org.cn/api/v1/mcp/2/DrugSDA-Toolvisualize_proteinfromserver-2(streamable-http) -https://scp.intern-ai.org.cn/api/v1/mcp/2/DrugSDA-Toolvisualize_complexfromserver-2(streamable-http) -https://scp.intern-ai.org.cn/api/v1/mcp/2/DrugSDA-Tool
Workflow
- Convert SMILES to SDF
- Visualize small molecule
- Visualize protein
- Visualize protein-ligand complex
Test Case
Input
{
"smiles": "CC(=O)Oc1ccccc1C(=O)O",
"pdb_code": "1AKE"
}
Expected Steps
- Convert SMILES to SDF
- Visualize small molecule
- Visualize protein
- Visualize protein-ligand complex
Usage Example
Note: Replace
sk-b04409a1-b32b-4511-9aeb-22980abdc05cwith your own SCP Hub API Key. You can obtain one from the SCP Platform.
import asyncio
import json
from contextlib import AsyncExitStack
from mcp import ClientSession
from mcp.client.streamable_http import streamablehttp_client
from mcp.client.sse import sse_client
SERVERS = {
"server-2": "https://scp.intern-ai.org.cn/api/v1/mcp/2/DrugSDA-Tool"
}
async def connect(url, stack):
transport = streamablehttp_client(url=url, headers={"SCP-HUB-API-KEY": "sk-b04409a1-b32b-4511-9aeb-22980abdc05c"})
read, write, _ = await stack.enter_async_context(transport)
ctx = ClientSession(read, write)
session = await stack.enter_async_context(ctx)
await session.initialize()
return session
def 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.text
return str(result)
except: return str(result)
async def main():
async with AsyncExitStack() as stack:
# Connect to required servers
sessions = {}
sessions["server-2"] = await connect("https://scp.intern-ai.org.cn/api/v1/mcp/2/DrugSDA-Tool", stack)
# Execute workflow steps
# Step 1: Convert SMILES to SDF
result_1 = await sessions["server-2"].call_tool("convert_smiles_to_format", arguments={})
data_1 = parse(result_1)
print(f"Step 1 result: {json.dumps(data_1, indent=2, ensure_ascii=False)[:500]}")
# Step 2: Visualize small molecule
result_2 = await sessions["server-2"].call_tool("visualize_molecule", arguments={})
data_2 = parse(result_2)
print(f"Step 2 result: {json.dumps(data_2, indent=2, ensure_ascii=False)[:500]}")
# Step 3: Visualize protein
result_3 = await sessions["server-2"].call_tool("visualize_protein", arguments={})
data_3 = parse(result_3)
print(f"Step 3 result: {json.dumps(data_3, indent=2, ensure_ascii=False)[:500]}")
# Step 4: Visualize protein-ligand complex
result_4 = await sessions["server-2"].call_tool("visualize_complex", arguments={})
data_4 = parse(result_4)
print(f"Step 4 result: {json.dumps(data_4, indent=2, ensure_ascii=False)[:500]}")
# Cleanup
print("Workflow complete!")
if __name__ == "__main__":
asyncio.run(main())
technical
- github
- SpectrAI-Initiative/InnoClaw
- stars
- 374
- license
- Apache-2.0
- contributors
- 16
- last commit
- 2026-04-20T01:27:21Z
- file
- .claude/skills/molecular_visualization_suite/SKILL.md