fda-drug-risk-assessment
community[skill]
Assess drug risks and adverse effects using FDA drug database to retrieve safety information and risk profiles.
$
/plugin install InnoClawdetails
FDA Drug Risk Assessment
Usage
1. MCP Server Definition
import asyncio
import json
from contextlib import AsyncExitStack
from mcp.client.streamable_http import streamablehttp_client
from mcp import ClientSession
class OrigeneClient:
"""Origene-FDADrug MCP Client"""
def __init__(self, server_url: str, api_key: str):
self.server_url = server_url
self.api_key = api_key
self.session = None
async def connect(self):
try:
self.transport = streamablehttp_client(
url=self.server_url,
headers={"SCP-HUB-API-KEY": self.api_key}
)
self._stack = AsyncExitStack()
await self._stack.__aenter__()
self.read, self.write, self.get_session_id = await self._stack.enter_async_context(self.transport)
self.session_ctx = ClientSession(self.read, self.write)
self.session = await self._stack.enter_async_context(self.session_ctx)
await self.session.initialize()
return True
except Exception as e:
print(f"✗ connect failure: {e}")
return False
async def disconnect(self):
"""Disconnect from server"""
try:
if hasattr(self, '_stack'):
await self._stack.aclose()
print("✓ already disconnect")
except Exception as e:
print(f"✗ disconnect error: {e}")
def parse_result(self, result):
if isinstance(result, dict):
content_list = result.get("content") or []
else:
content_list = getattr(result, "content", []) or []
texts = []
for item in content_list:
if isinstance(item, dict):
if item.get("type") == "text":
texts.append(item.get("text") or "")
else:
if getattr(item, "type", None) == "text":
texts.append(getattr(item, "text", "") or "")
return "".join(texts)
2. Drug Risk Assessment Workflow
Implementation:
## Initialize client
client = OrigeneClient(
"https://scp.intern-ai.org.cn/api/v1/mcp/14/Origene-FDADrug",
"<your-api-key>"
)
if not await client.connect():
print("connection failed")
exit()
## Get drug risk information
result = await client.session.call_tool(
"get_risk_info_by_drug_name",
arguments={
"drug_name": "Valsartan"
}
)
result_data = client.parse_result(result)
print(result_data)
await client.disconnect()
Tool Descriptions
Origene-FDADrug Server:
get_risk_info_by_drug_name: Retrieve FDA drug risk information- Args:
drug_name(str): FDA approved drug name
- Returns: Risk profile, adverse events, and safety data
- Args:
Use Cases
- Drug safety assessment
- Adverse effect analysis
- Pharmacovigilance
- Clinical decision support
technical
- github
- SpectrAI-Initiative/InnoClaw
- stars
- 374
- license
- Apache-2.0
- contributors
- 16
- last commit
- 2026-04-20T01:27:21Z
- file
- .claude/skills/fda-drug-risk-assessment/SKILL.md