pharmacokinetics-profile

Pharmacokinetics Profile Builder - Build a PK profile: FDA pharmacokinetics, clinical pharmacology, dosage info, and molecular properties. Use this skill for pharmacology tasks involving get pharmacokinetics by drug name get clinical pharmacology by drug name get dosage and storage information by drug name get compound by name. Combines 4 tools from 2 SCP server(s).

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Repository: SpectrAI-Initiative/InnoClaw
Last source activity: April 1, 2026 at 17:03
Detected SKILL.md language: English
Stars: 390
Forks: 28

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name	pharmacokinetics_profile
description	Pharmacokinetics Profile Builder - Build a PK profile: FDA pharmacokinetics, clinical pharmacology, dosage info, and molecular properties. Use this skill for pharmacology tasks involving get pharmacokinetics by drug name get clinical pharmacology by drug name get dosage and storage information by drug name get compound by name. Combines 4 tools from 2 SCP server(s).

Pharmacokinetics Profile Builder

Discipline: Pharmacology | Tools Used: 4 | Servers: 2

Description

Build a PK profile: FDA pharmacokinetics, clinical pharmacology, dosage info, and molecular properties.

Tools Used

get_pharmacokinetics_by_drug_name from fda-drug-server (streamable-http) - https://scp.intern-ai.org.cn/api/v1/mcp/14/Origene-FDADrug
get_clinical_pharmacology_by_drug_name from fda-drug-server (streamable-http) - https://scp.intern-ai.org.cn/api/v1/mcp/14/Origene-FDADrug
get_dosage_and_storage_information_by_drug_name from fda-drug-server (streamable-http) - https://scp.intern-ai.org.cn/api/v1/mcp/14/Origene-FDADrug
get_compound_by_name from pubchem-server (streamable-http) - https://scp.intern-ai.org.cn/api/v1/mcp/8/Origene-PubChem

Workflow

Get PK data from FDA
Get clinical pharmacology
Get dosage info
Get molecular structure from PubChem

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", "pubchem-server": "https://scp.intern-ai.org.cn/api/v1/mcp/8/Origene-PubChem" } 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) sessions["pubchem-server"] = await connect("https://scp.intern-ai.org.cn/api/v1/mcp/8/Origene-PubChem", stack) # Execute workflow steps # Step 1: Get PK data from FDA 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 clinical pharmacology result_2 = await sessions["fda-drug-server"].call_tool("get_clinical_pharmacology_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 dosage info result_3 = await sessions["fda-drug-server"].call_tool("get_dosage_and_storage_information_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 molecular structure from PubChem result_4 = await sessions["pubchem-server"].call_tool("get_compound_by_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())

pharmacokinetics-profile

Install options

Review the source files

Pharmacokinetics Profile Builder

Description

Tools Used

Workflow

Test Case

Input

Pharmacokinetics Profile Builder

Description

Tools Used

Workflow

Test Case

Input

Expected Steps

Usage Example

pharmacokinetics-profile

Source facts

Install options

Review the source files

More from this repository

More from this repository

Pharmacokinetics Profile Builder

Description

Tools Used

Workflow

Test Case

Input

Pharmacokinetics Profile Builder

Description

Tools Used

Workflow

Test Case

Input

Expected Steps

Usage Example