clinical_pharmacology_report
community[skill]
Clinical Pharmacology Report - Generate clinical pharmacology report: PK, PD, mechanism, drug interactions, and special populations. Use this skill for clinical pharmacology tasks involving get pharmacokinetics by drug name get pharmacodynamics by drug name get mechanism of action by drug name get drug interactions by drug name get geriatric use info by drug name. Combines 5 tools from 1 SCP server(s).
$
/plugin install InnoClawdetails
Clinical Pharmacology Report
Discipline: Clinical Pharmacology | Tools Used: 5 | Servers: 1
Description
Generate clinical pharmacology report: PK, PD, mechanism, drug interactions, and special populations.
Tools Used
get_pharmacokinetics_by_drug_namefromfda-drug-server(streamable-http) -https://scp.intern-ai.org.cn/api/v1/mcp/14/Origene-FDADrugget_pharmacodynamics_by_drug_namefromfda-drug-server(streamable-http) -https://scp.intern-ai.org.cn/api/v1/mcp/14/Origene-FDADrugget_mechanism_of_action_by_drug_namefromfda-drug-server(streamable-http) -https://scp.intern-ai.org.cn/api/v1/mcp/14/Origene-FDADrugget_drug_interactions_by_drug_namefromfda-drug-server(streamable-http) -https://scp.intern-ai.org.cn/api/v1/mcp/14/Origene-FDADrugget_geriatric_use_info_by_drug_namefromfda-drug-server(streamable-http) -https://scp.intern-ai.org.cn/api/v1/mcp/14/Origene-FDADrug
Workflow
- Get pharmacokinetics
- Get pharmacodynamics
- Get mechanism of action
- Get drug interactions
- Get geriatric use data
Test Case
Input
{
"drug_name": "metformin"
}
Expected Steps
- Get pharmacokinetics
- Get pharmacodynamics
- Get mechanism of action
- Get drug interactions
- Get geriatric use data
Usage Example
Note: Replace
sk-b04409a1-b32b-4511-9aeb-22980abdc05cwith your own SCP Hub API Key. You can obtain one from the SCP Platform.
import asyncio
import json
from contextlib import AsyncExitStack
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, stack):
transport = streamablehttp_client(url=url, headers={"SCP-HUB-API-KEY": "sk-b04409a1-b32b-4511-9aeb-22980abdc05c"})
read, write, _ = await stack.enter_async_context(transport)
ctx = ClientSession(read, write)
session = await stack.enter_async_context(ctx)
await session.initialize()
return session
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():
async with AsyncExitStack() as stack:
# Connect to required servers
sessions = {}
sessions["fda-drug-server"] = await connect("https://scp.intern-ai.org.cn/api/v1/mcp/14/Origene-FDADrug", stack)
# Execute workflow steps
# Step 1: Get pharmacokinetics
result_1 = await sessions["fda-drug-server"].call_tool("get_pharmacokinetics_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 pharmacodynamics
result_2 = await sessions["fda-drug-server"].call_tool("get_pharmacodynamics_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 mechanism of action
result_3 = await sessions["fda-drug-server"].call_tool("get_mechanism_of_action_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 drug interactions
result_4 = await sessions["fda-drug-server"].call_tool("get_drug_interactions_by_drug_name", arguments={})
data_4 = parse(result_4)
print(f"Step 4 result: {json.dumps(data_4, indent=2, ensure_ascii=False)[:500]}")
# Step 5: Get geriatric use data
result_5 = await sessions["fda-drug-server"].call_tool("get_geriatric_use_info_by_drug_name", arguments={})
data_5 = parse(result_5)
print(f"Step 5 result: {json.dumps(data_5, indent=2, ensure_ascii=False)[:500]}")
# Cleanup
print("Workflow complete!")
if __name__ == "__main__":
asyncio.run(main())
technical
- github
- SpectrAI-Initiative/InnoClaw
- stars
- 374
- license
- Apache-2.0
- contributors
- 16
- last commit
- 2026-04-20T01:27:21Z
- file
- .claude/skills/clinical_pharmacology_report/SKILL.md