Comprehensive Drug Safety Profile

SkillProductivity

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).

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the Comprehensive Drug Safety Profile skill

What this skill tells your AI

The instructions your AI receives, as published by internscience/scp in skills/drug_safety_profile/SKILL.md and read by ahel’s review.

Discipline: Pharmacology | Tools Used: 4 | Servers: 1

Description

Build a complete drug safety profile by combining FDA adverse reactions, boxed warnings, drug interactions, and contraindications.

Tools Used

  • get_adverse_reactions_by_drug_name from fda-drug-server (streamable-http) - https://scp.intern-ai.org.cn/api/v1/mcp/14/Origene-FDADrug
  • get_boxed_warning_info_by_drug_name from fda-drug-server (streamable-http) - https://scp.intern-ai.org.cn/api/v1/mcp/14/Origene-FDADrug
  • 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_contraindications_by_drug_name from fda-drug-server (streamable-http) - https://scp.intern-ai.org.cn/api/v1/mcp/14/Origene-FDADrug

Workflow

  1. Get adverse reactions
  2. Get boxed warnings
  3. Get drug interactions
  4. Get contraindications

Test Case

Input

{
    "drug_name": "metformin"
}

Expected Steps

  1. Get adverse reactions
  2. Get boxed warnings
  3. Get drug interactions
  4. Get contraindications

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"
}

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())

Signals

GitHub stars
167
Forks
9
Last commit
Jun 2026
Advanced
Catalog kind
skill
Gateway key
drug-safety-profile
Source
github.com/internscience/scp