drug_safety_profile: Скилл для анализа безопасности лекарств

--- name: drug_safety_profile description: "Comprehensive Drug Safety Profile - Build a complete drug safety profile by combining FDA adverse reactions, boxed warnings, drug interactions, and contraindications. Use this skill for pharmacology tasks involving get adverse reactions by drug name get boxed warning info by drug name get drug interactions by drug name get contraindications by drug name. Combines 4 tools from 1 SCP server(s)." --- # Comprehensive Drug Safety Profile **Discipline**: Pharmacology | **Tools Used**: 4 | **Servers**: 1 ## Description Build a complete drug safety profile by combining FDA adverse reactions, boxed warnings, drug interactions, and contraindications. ## Tools Used - **`get_adverse_reactions_by_drug_name`** from `fda-drug-server` (streamable-http) - `https://scp.intern-ai.org.cn/api/v1/mcp/14/Origene-FDADrug` - **`get_boxed_warning_info_by_drug_name`** from `fda-drug-server` (streamable-http) - `https://scp.intern-ai.org.cn/api/v1/mcp/14/Origene-FDADrug` - **`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_contraindications_by_drug_name`** from `fda-drug-server` (streamable-http) - `https://scp.intern-ai.org.cn/api/v1/mcp/14/Origene-FDADrug` ## Workflow 1. Get adverse reactions 2. Get boxed warnings 3. Get drug interactions 4. Get contraindications ## Test Case ### Input ```json { "drug_name": "metformin" } ``` ### Expected Steps 1. Get adverse reactions 2. Get boxed warnings 3. Get drug interactions 4. Get contraindications ## 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" } 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 adverse reactions result_1 = await sessions["fda-drug-server"].call_tool("get_adverse_reactions_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 boxed warnings result_2 = await sessions["fda-drug-server"].call_tool("get_boxed_warning_info_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 drug interactions result_3 = await sessions["fda-drug-server"].call_tool("get_drug_interactions_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 contraindications result_4 = await sessions["fda-drug-server"].call_tool("get_contraindications_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()) ```