Drug-Drug Interaction Checker
SkillDev toolsLets your agent check interactions between multiple drugs using FDA and PubChem data.
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Details
Instructions available. Your AI can read the instructions. Execution depends on the setup they require.
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About this skill
The largest open-source medical AI skills library for OpenClaw🦞.
What this skill tells your AI
The instructions your AI receives, as published by freedomintelligence/openclaw-medical-skills in skills/drug-interaction-checker/SKILL.md and read by Ahel’s review.
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_namefromfda-drug-server(streamable-http) -https://scp.intern-ai.org.cn/api/v1/mcp/14/Origene-FDADrugget_compound_by_namefrompubchem-server(streamable-http) -https://scp.intern-ai.org.cn/api/v1/mcp/8/Origene-PubChemget_target_by_namefromchembl-server(streamable-http) -https://scp.intern-ai.org.cn/api/v1/mcp/4/Origene-ChEMBL
Workflow
- Get interactions for drug A
- Get interactions for drug B
- Compare compound targets from ChEMBL
Test Case
Input
{
"drug_a": "warfarin",
"drug_b": "aspirin"
}
Expected Steps
- Get interactions for drug A
- Get interactions for drug B
- 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.
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())
Signals
- GitHub stars
- 3k
- Forks
- 412
- Last commit
- Jul 2026
Others that do the same job
Advanced
- Item type
- skill
- Key
drug-interaction-checker- Source
- github.com/freedomintelligence/openclaw-medical-skills
github.com/freedomintelligence/openclaw-medical-skills
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