Functional Group Profiling
SkillProductivityFunctional 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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What this skill tells your AI
The instructions your AI receives, as published by spectrai-initiative/innoclaw in .claude/skills/functional_group_profiling/SKILL.md and read by ahel’s review.
Discipline: Organic Chemistry | Tools Used: 4 | Servers: 2
Description
Profile functional groups: radical assignment, H-bond analysis, aromaticity, and abbreviation condensation.
Tools Used
AssignRadicalsfromserver-31(sse) -https://scp.intern-ai.org.cn/api/v1/mcp/31/SciToolAgent-ChemGetHBANumfromserver-31(sse) -https://scp.intern-ai.org.cn/api/v1/mcp/31/SciToolAgent-ChemAromaticityAnalyzerfromserver-28(sse) -https://scp.intern-ai.org.cn/api/v1/mcp/28/InternAgentCondenseAbbreviationSubstanceGroupsfromserver-31(sse) -https://scp.intern-ai.org.cn/api/v1/mcp/31/SciToolAgent-Chem
Workflow
- Assign radical sites
- Count H-bond acceptors
- Analyze aromaticity
- Condense substance groups
Test Case
Input
{
"smiles": "CC(=O)Oc1ccccc1C(=O)O"
}
Expected Steps
- Assign radical sites
- Count H-bond acceptors
- Analyze aromaticity
- Condense substance groups
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-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, 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-31"] = await connect("https://scp.intern-ai.org.cn/api/v1/mcp/31/SciToolAgent-Chem", stack)
sessions["server-28"] = await connect("https://scp.intern-ai.org.cn/api/v1/mcp/28/InternAgent", stack)
# 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())
Signals
- GitHub stars
- 391
- Forks
- 28
- Last commit
- Aug 2026
Advanced
- Catalog kind
- skill
- Gateway key
functional-group-profiling-spectrai-initiative- Source
- github.com/spectrai-initiative/innoclaw