molecular-visualization-suite
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).
ソース情報
- リポジトリ
- InternScience/scp
- ソースの最終更新活動
- 2026年3月3日 09:51
- 検出された SKILL.md の言語
- 英語
- スター
- 173
- フォーク
- 11
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ソースの指示 · 読み取り専用プレビュー- name
- molecular_visualization_suite
- description
- 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).
# 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_format`** from `server-2` (streamable-http) - `https://scp.intern-ai.org.cn/api/v1/mcp/2/DrugSDA-Tool`
- **`visualize_molecule`** from `server-2` (streamable-http) - `https://scp.intern-ai.org.cn/api/v1/mcp/2/DrugSDA-Tool`
- **`visualize_protein`** from `server-2` (streamable-http) - `https://scp.intern-ai.org.cn/api/v1/mcp/2/DrugSDA-Tool`
- **`visualize_complex`** from `server-2` (streamable-http) - `https://scp.intern-ai.org.cn/api/v1/mcp/2/DrugSDA-Tool`
## Workflow
1. Convert SMILES to SDF
2. Visualize small molecule
3. Visualize protein
4. Visualize protein-ligand complex
## Test Case
### Input
```json
{
"smiles": "CC(=O)Oc1ccccc1C(=O)O",
"pdb_code": "1AKE"
}
```
### Expected Steps
1. Convert SMILES to SDF
2. Visualize small molecule
3. Visualize protein
4. Visualize protein-ligand complex
## Usage Example
> **Note:** Replace `<YOUR_SCP_HUB_API_KEY>` with your own SCP Hub API Key. You can obtain one from the [SCP Platform](https://scphub.intern-ai.org.cn).
```python
import asyncio
import json
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, 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, transport
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():
# Connect to required servers
sessions = {}
sessions["server-2"], _, _ = await connect("https://scp.intern-ai.org.cn/api/v1/mcp/2/DrugSDA-Tool", "streamable-http")
# 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())
```
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