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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).

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InternScience/scp
最近来源活动
2026年3月3日 09:51
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SKILL.md
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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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