# Drug Safety Profile

> 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).

- Skill: `internscience/drug-safety-profile` (Agent Skill)
- Install (CLI): `npx skillmds@latest add internscience/drug-safety-profile`
- Raw SKILL.md: https://api.skillmd.com/api/skills/internscience/drug-safety-profile/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Coding & Dev Tools
- Author: internscience (https://skillmd.com/u/internscience)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/internscience/drug-safety-profile

---


# Comprehensive Drug Safety Profile

**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
```json
{
    "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](https://scphub.intern-ai.org.cn).

```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"
}

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())
```