skills/drug_safety_profile/SKILL.md
Comprehensive Drug Safety Profile - Build a complete drug safety profile by combining FDA adverse reactions, boxed warnings, drug interactions, and contraindications. Use this skill for pharmacology tasks involving get adverse reactions by drug name get boxed warning info by drug name get drug interactions by drug name get contraindications by drug name. Combines 4 tools from 1 SCP server(s).
npx skillsauth add InternScience/scp drug_safety_profileInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Discipline: Pharmacology | Tools Used: 4 | Servers: 1
Build a complete drug safety profile by combining FDA adverse reactions, boxed warnings, drug interactions, and contraindications.
get_adverse_reactions_by_drug_name from fda-drug-server (streamable-http) - https://scp.intern-ai.org.cn/api/v1/mcp/14/Origene-FDADrugget_boxed_warning_info_by_drug_name from fda-drug-server (streamable-http) - https://scp.intern-ai.org.cn/api/v1/mcp/14/Origene-FDADrugget_drug_interactions_by_drug_name from fda-drug-server (streamable-http) - https://scp.intern-ai.org.cn/api/v1/mcp/14/Origene-FDADrugget_contraindications_by_drug_name from fda-drug-server (streamable-http) - https://scp.intern-ai.org.cn/api/v1/mcp/14/Origene-FDADrug{
"drug_name": "metformin"
}
Note: Replace
<YOUR_SCP_HUB_API_KEY>with your own SCP Hub API Key. You can obtain one from the SCP Platform.
import asyncio
import json
from mcp import ClientSession
from mcp.client.streamable_http import streamablehttp_client
from mcp.client.sse import sse_client
SERVERS = {
"fda-drug-server": "https://scp.intern-ai.org.cn/api/v1/mcp/14/Origene-FDADrug"
}
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["fda-drug-server"], _, _ = await connect("https://scp.intern-ai.org.cn/api/v1/mcp/14/Origene-FDADrug", "streamable-http")
# Execute workflow steps
# Step 1: Get adverse reactions
result_1 = await sessions["fda-drug-server"].call_tool("get_adverse_reactions_by_drug_name", arguments={})
data_1 = parse(result_1)
print(f"Step 1 result: {json.dumps(data_1, indent=2, ensure_ascii=False)[:500]}")
# Step 2: Get boxed warnings
result_2 = await sessions["fda-drug-server"].call_tool("get_boxed_warning_info_by_drug_name", arguments={})
data_2 = parse(result_2)
print(f"Step 2 result: {json.dumps(data_2, indent=2, ensure_ascii=False)[:500]}")
# Step 3: Get drug interactions
result_3 = await sessions["fda-drug-server"].call_tool("get_drug_interactions_by_drug_name", arguments={})
data_3 = parse(result_3)
print(f"Step 3 result: {json.dumps(data_3, indent=2, ensure_ascii=False)[:500]}")
# Step 4: Get contraindications
result_4 = await sessions["fda-drug-server"].call_tool("get_contraindications_by_drug_name", 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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