clinical-trial-drug-profile

Clinical Trial Drug Profiling - Profile drug for clinical trials: FDA clinical studies, contraindications, pregnancy info, and geriatric use. Use this skill for clinical research tasks involving get clinical studies info by drug name get contraindications by drug name get pregnancy effects info by drug name get geriatric use info by drug name. Combines 4 tools from 1 SCP server(s).

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Repository: SpectrAI-Initiative/InnoClaw
Letzte Quellaktivität: 1. April 2026 um 17:03
Erkannte Sprache von SKILL.md: Englisch
Sterne: 390
Forks: 28

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npx skills add https://github.com/SpectrAI-Initiative/InnoClaw --skill clinical-trial-drug-profile

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name	clinical_trial_drug_profile
description	Clinical Trial Drug Profiling - Profile drug for clinical trials: FDA clinical studies, contraindications, pregnancy info, and geriatric use. Use this skill for clinical research tasks involving get clinical studies info by drug name get contraindications by drug name get pregnancy effects info by drug name get geriatric use info by drug name. Combines 4 tools from 1 SCP server(s).

Clinical Trial Drug Profiling

Discipline: Clinical Research | Tools Used: 4 | Servers: 1

Description

Profile drug for clinical trials: FDA clinical studies, contraindications, pregnancy info, and geriatric use.

Tools Used

get_clinical_studies_info_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
get_pregnancy_effects_info_by_drug_name from fda-drug-server (streamable-http) - https://scp.intern-ai.org.cn/api/v1/mcp/14/Origene-FDADrug
get_geriatric_use_info_by_drug_name from fda-drug-server (streamable-http) - https://scp.intern-ai.org.cn/api/v1/mcp/14/Origene-FDADrug

Workflow

Get clinical studies info
Get contraindications
Get pregnancy effects
Get geriatric use info

Test Case

Input

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 clinical studies info result_1 = await sessions["fda-drug-server"].call_tool("get_clinical_studies_info_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 contraindications result_2 = await sessions["fda-drug-server"].call_tool("get_contraindications_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 pregnancy effects result_3 = await sessions["fda-drug-server"].call_tool("get_pregnancy_effects_info_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 geriatric use info result_4 = await sessions["fda-drug-server"].call_tool("get_geriatric_use_info_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())

clinical-trial-drug-profile

Installationsoptionen

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Clinical Trial Drug Profiling

Description

Tools Used

Workflow

Test Case

Input

Clinical Trial Drug Profiling

Description

Tools Used

Workflow

Test Case

Input

Expected Steps

Usage Example

clinical-trial-drug-profile

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Installationsoptionen

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Clinical Trial Drug Profiling

Description

Tools Used

Workflow

Test Case

Input

Clinical Trial Drug Profiling

Description

Tools Used

Workflow

Test Case

Input

Expected Steps

Usage Example