drug_interaction_checker: Скилл проверки взаимодействий лекарств

--- name: drug_interaction_checker description: "Drug-Drug Interaction Checker - Check interactions between multiple drugs using FDA interaction data, PubChem compound info, and ChEMBL target overlap analysis. Use this skill for clinical pharmacology tasks involving get drug interactions by drug name get compound by name get target by name. Combines 3 tools from 3 SCP server(s)." --- # Drug-Drug Interaction Checker **Discipline**: Clinical Pharmacology | **Tools Used**: 3 | **Servers**: 3 ## Description Check interactions between multiple drugs using FDA interaction data, PubChem compound info, and ChEMBL target overlap analysis. ## Tools Used - **`get_drug_interactions_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` - **`get_target_by_name`** from `chembl-server` (streamable-http) - `https://scp.intern-ai.org.cn/api/v1/mcp/4/Origene-ChEMBL` ## Workflow 1. Get interactions for drug A 2. Get interactions for drug B 3. Compare compound targets from ChEMBL ## Test Case ### Input ```json { "drug_a": "warfarin", "drug_b": "aspirin" } ``` ### Expected Steps 1. Get interactions for drug A 2. Get interactions for drug B 3. Compare compound targets from ChEMBL ## Usage Example > **Note:** Replace `sk-b04409a1-b32b-4511-9aeb-22980abdc05c` with your own SCP Hub API Key. You can obtain one from the [SCP Platform](https://scphub.intern-ai.org.cn). ```python 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", "chembl-server": "https://scp.intern-ai.org.cn/api/v1/mcp/4/Origene-ChEMBL" } 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) sessions["chembl-server"] = await connect("https://scp.intern-ai.org.cn/api/v1/mcp/4/Origene-ChEMBL", stack) # Execute workflow steps # Step 1: Get interactions for drug A result_1 = await sessions["fda-drug-server"].call_tool("get_drug_interactions_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 interactions for drug B result_2 = await sessions["pubchem-server"].call_tool("get_compound_by_name", arguments={}) data_2 = parse(result_2) print(f"Step 2 result: {json.dumps(data_2, indent=2, ensure_ascii=False)[:500]}") # Step 3: Compare compound targets from ChEMBL result_3 = await sessions["chembl-server"].call_tool("get_target_by_name", arguments={}) data_3 = parse(result_3) print(f"Step 3 result: {json.dumps(data_3, indent=2, ensure_ascii=False)[:500]}") # Cleanup print("Workflow complete!") if __name__ == "__main__": asyncio.run(main()) ```