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functional-group-profiling

Functional Group Profiling - Profile functional groups: radical assignment, H-bond analysis, aromaticity, and abbreviation condensation. Use this skill for organic chemistry tasks involving AssignRadicals GetHBANum AromaticityAnalyzer CondenseAbbreviationSubstanceGroups. Combines 4 tools from 2 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
functional_group_profiling
description
Functional Group Profiling - Profile functional groups: radical assignment, H-bond analysis, aromaticity, and abbreviation condensation. Use this skill for organic chemistry tasks involving AssignRadicals GetHBANum AromaticityAnalyzer CondenseAbbreviationSubstanceGroups. Combines 4 tools from 2 SCP server(s).
# Functional Group Profiling **Discipline**: Organic Chemistry | **Tools Used**: 4 | **Servers**: 2 ## Description Profile functional groups: radical assignment, H-bond analysis, aromaticity, and abbreviation condensation. ## Tools Used - **`AssignRadicals`** from `server-31` (sse) - `https://scp.intern-ai.org.cn/api/v1/mcp/31/SciToolAgent-Chem` - **`GetHBANum`** from `server-31` (sse) - `https://scp.intern-ai.org.cn/api/v1/mcp/31/SciToolAgent-Chem` - **`AromaticityAnalyzer`** from `server-28` (sse) - `https://scp.intern-ai.org.cn/api/v1/mcp/28/InternAgent` - **`CondenseAbbreviationSubstanceGroups`** from `server-31` (sse) - `https://scp.intern-ai.org.cn/api/v1/mcp/31/SciToolAgent-Chem` ## Workflow 1. Assign radical sites 2. Count H-bond acceptors 3. Analyze aromaticity 4. Condense substance groups ## Test Case ### Input ```json { "smiles": "CC(=O)Oc1ccccc1C(=O)O" } ``` ### Expected Steps 1. Assign radical sites 2. Count H-bond acceptors 3. Analyze aromaticity 4. Condense substance groups ## 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-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" } 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-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") # Execute workflow steps # Step 1: Assign radical sites result_1 = await sessions["server-31"].call_tool("AssignRadicals", arguments={}) data_1 = parse(result_1) print(f"Step 1 result: {json.dumps(data_1, indent=2, ensure_ascii=False)[:500]}") # Step 2: Count H-bond acceptors result_2 = await sessions["server-31"].call_tool("GetHBANum", arguments={}) data_2 = parse(result_2) print(f"Step 2 result: {json.dumps(data_2, indent=2, ensure_ascii=False)[:500]}") # Step 3: Analyze aromaticity result_3 = await sessions["server-28"].call_tool("AromaticityAnalyzer", arguments={}) data_3 = parse(result_3) print(f"Step 3 result: {json.dumps(data_3, indent=2, ensure_ascii=False)[:500]}") # Step 4: Condense substance groups result_4 = await sessions["server-31"].call_tool("CondenseAbbreviationSubstanceGroups", 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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