.claude/skills/pubchem_deep_dive/SKILL.md
PubChem Deep Dive Analysis - Deep dive into PubChem: compound info, bioassay summary, 3D conformers, synonyms, and general description. Use this skill for chemical databases tasks involving get pubchem compound by cid get assay summary by cid get conformers by cid get compound synonyms by name get general info by compound name. Combines 5 tools from 1 SCP server(s).
npx skillsauth add SpectrAI-Initiative/InnoClaw pubchem_deep_diveInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Discipline: Chemical Databases | Tools Used: 5 | Servers: 1
Deep dive into PubChem: compound info, bioassay summary, 3D conformers, synonyms, and general description.
get_pubchem_compound_by_cid from pubchem-server (streamable-http) - https://scp.intern-ai.org.cn/api/v1/mcp/8/Origene-PubChemget_assay_summary_by_cid from pubchem-server (streamable-http) - https://scp.intern-ai.org.cn/api/v1/mcp/8/Origene-PubChemget_conformers_by_cid from pubchem-server (streamable-http) - https://scp.intern-ai.org.cn/api/v1/mcp/8/Origene-PubChemget_compound_synonyms_by_name from pubchem-server (streamable-http) - https://scp.intern-ai.org.cn/api/v1/mcp/8/Origene-PubChemget_general_info_by_compound_name from pubchem-server (streamable-http) - https://scp.intern-ai.org.cn/api/v1/mcp/8/Origene-PubChem{
"compound_name": "aspirin",
"cid": 2244
}
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 = {
"pubchem-server": "https://scp.intern-ai.org.cn/api/v1/mcp/8/Origene-PubChem"
}
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["pubchem-server"] = await connect("https://scp.intern-ai.org.cn/api/v1/mcp/8/Origene-PubChem", stack)
# Execute workflow steps
# Step 1: Get full compound info
result_1 = await sessions["pubchem-server"].call_tool("get_pubchem_compound_by_cid", arguments={})
data_1 = parse(result_1)
print(f"Step 1 result: {json.dumps(data_1, indent=2, ensure_ascii=False)[:500]}")
# Step 2: Get bioassay summary
result_2 = await sessions["pubchem-server"].call_tool("get_assay_summary_by_cid", arguments={})
data_2 = parse(result_2)
print(f"Step 2 result: {json.dumps(data_2, indent=2, ensure_ascii=False)[:500]}")
# Step 3: Get 3D conformers
result_3 = await sessions["pubchem-server"].call_tool("get_conformers_by_cid", arguments={})
data_3 = parse(result_3)
print(f"Step 3 result: {json.dumps(data_3, indent=2, ensure_ascii=False)[:500]}")
# Step 4: Get all synonyms
result_4 = await sessions["pubchem-server"].call_tool("get_compound_synonyms_by_name", arguments={})
data_4 = parse(result_4)
print(f"Step 4 result: {json.dumps(data_4, indent=2, ensure_ascii=False)[:500]}")
# Step 5: Get general description
result_5 = await sessions["pubchem-server"].call_tool("get_general_info_by_compound_name", arguments={})
data_5 = parse(result_5)
print(f"Step 5 result: {json.dumps(data_5, indent=2, ensure_ascii=False)[:500]}")
# Cleanup
print("Workflow complete!")
if __name__ == "__main__":
asyncio.run(main())
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