internscience/drclaw/drug-interaction-checker

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Drug-Drug Interaction Checker - Check interactions between multiple drugs using FDA interaction data, PubChem compound info, and ChEMBL target overlap analysis. Use this skill for clinical pharmacology tasks involving get drug interactions by drug name get compound by name get target by name. Combines 3 tools from 3 SCP server(s).

Install

npx vskill@latest install internscience/drclaw/drug-interaction-checker

SKILL.md

Drug-Drug Interaction Checker

Discipline: Clinical Pharmacology | Tools Used: 3 | Servers: 3

Description

Check interactions between multiple drugs using FDA interaction data, PubChem compound info, and ChEMBL target overlap analysis.

Tools Used

  • `get_drug_interactions_by_drug_name` from fda-drug-server (streamable-http) - https://scp.intern-ai.org.cn/api/v1/mcp/14/Origene-FDADrug
  • `get_compound_by_name` from pubchem-server (streamable-http) - https://scp.intern-ai.org.cn/api/v1/mcp/8/Origene-PubChem
  • `get_target_by_name` from chembl-server (streamable-http) - https://scp.intern-ai.org.cn/api/v1/mcp/4/Origene-ChEMBL

Workflow

  1. Get interactions for drug A
  2. Get interactions for drug B
  3. Compare compound targets from ChEMBL

Test Case

Input
json
{
"drug_a": "warfarin",
"drug_b": "aspirin"
}
Expected Steps
  1. Get interactions for drug A
  2. Get interactions for drug B
  3. Compare compound targets from ChEMBL

Usage Example

Note: Replace <YOUR_SCP_HUB_API_KEY> with your own SCP Hub API Key. You can obtain one from the SCP Platform.
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 = {
"fda-drug-server": "https://scp.intern-ai.org.cn/api/v1/mcp/14/Origene-FDADrug",
"pubchem-server": "https://scp.intern-ai.org.cn/api/v1/mcp/8/Origene-PubChem",
"chembl-server": "https://scp.intern-ai.org.cn/api/v1/mcp/4/Origene-ChEMBL"
}
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")
sessions["pubchem-server"], _, _ = await connect("https://scp.intern-ai.org.cn/api/v1/mcp/8/Origene-PubChem", "streamable-http")
sessions["chembl-server"], _, _ = await connect("https://scp.intern-ai.org.cn/api/v1/mcp/4/Origene-ChEMBL", "streamable-http")
# Execute workflow steps
# Step 1: Get interactions for drug A
result_1 = await sessions["fda-drug-server"].call_tool("get_drug_interactions_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 interactions for drug B
result_2 = await sessions["pubchem-server"].call_tool("get_compound_by_name", arguments={})
data_2 = parse(result_2)
print(f"Step 2 result: {json.dumps(data_2, indent=2, ensure_ascii=False)[:500]}")
# Step 3: Compare compound targets from ChEMBL
result_3 = await sessions["chembl-server"].call_tool("get_target_by_name", arguments={})
data_3 = parse(result_3)
print(f"Step 3 result: {json.dumps(data_3, indent=2, ensure_ascii=False)[:500]}")
# Cleanup
print("Workflow complete!")
if __name__ == "__main__":
asyncio.run(main())

Security

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  • Model reviewNot runA model review is scheduled for the next rescan.

Quality evaluation

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Source

Popularity

Repository stars
172
Repository forks
10
7-day trend score
26

Stars and forks are for the whole GitHub repository, not this skill alone. Refreshed 12 Jun 2026, 4 months ago.

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