FDA Drug Risk Assessment

SkillDatabases & data

Assess drug risks and adverse effects using FDA drug database to retrieve safety information and risk profiles.

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 FDA Drug Risk Assessment skill

What this skill tells your AI

The instructions your AI receives, as published by spectrai-initiative/innoclaw in .claude/skills/fda-drug-risk-assessment/SKILL.md and read by ahel’s review.

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

Use Cases

  • Drug safety assessment
  • Adverse effect analysis
  • Pharmacovigilance
  • Clinical decision support

Signals

GitHub stars
391
Forks
28
Last commit
Aug 2026
Advanced
Catalog kind
skill
Gateway key
fda-drug-risk-assessment-spectrai-initiative
Source
github.com/spectrai-initiative/innoclaw