chemical_safety_assessment: Скилл оценки безопасности химических веществ

--- name: chemical_safety_assessment description: "Chemical Safety Assessment - Assess chemical safety: PubChem compound info, FDA drug data, ADMET prediction, and structural alerts from ChEMBL. Use this skill for chemical safety tasks involving get general info by compound name get warnings and cautions by drug name pred molecule admet get compound structural alert. Combines 4 tools from 4 SCP server(s)." --- # Chemical Safety Assessment **Discipline**: Chemical Safety | **Tools Used**: 4 | **Servers**: 4 ## Description Assess chemical safety: PubChem compound info, FDA drug data, ADMET prediction, and structural alerts from ChEMBL. ## Tools Used - **`get_general_info_by_compound_name`** from `pubchem-server` (streamable-http) - `https://scp.intern-ai.org.cn/api/v1/mcp/8/Origene-PubChem` - **`get_warnings_and_cautions_by_drug_name`** from `fda-drug-server` (streamable-http) - `https://scp.intern-ai.org.cn/api/v1/mcp/14/Origene-FDADrug` - **`pred_molecule_admet`** from `server-3` (streamable-http) - `https://scp.intern-ai.org.cn/api/v1/mcp/3/DrugSDA-Model` - **`get_compound_structural_alert`** from `chembl-server` (streamable-http) - `https://scp.intern-ai.org.cn/api/v1/mcp/4/Origene-ChEMBL` ## Workflow 1. Get PubChem compound info 2. Get FDA warnings 3. Predict ADMET toxicity 4. Check structural alerts from ChEMBL ## Test Case ### Input ```json { "compound_name": "acetaminophen", "smiles": "CC(=O)Nc1ccc(O)cc1" } ``` ### Expected Steps 1. Get PubChem compound info 2. Get FDA warnings 3. Predict ADMET toxicity 4. Check structural alerts 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 = { "pubchem-server": "https://scp.intern-ai.org.cn/api/v1/mcp/8/Origene-PubChem", "fda-drug-server": "https://scp.intern-ai.org.cn/api/v1/mcp/14/Origene-FDADrug", "server-3": "https://scp.intern-ai.org.cn/api/v1/mcp/3/DrugSDA-Model", "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["pubchem-server"] = await connect("https://scp.intern-ai.org.cn/api/v1/mcp/8/Origene-PubChem", stack) sessions["fda-drug-server"] = await connect("https://scp.intern-ai.org.cn/api/v1/mcp/14/Origene-FDADrug", stack) sessions["server-3"] = await connect("https://scp.intern-ai.org.cn/api/v1/mcp/3/DrugSDA-Model", 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 PubChem compound info result_1 = await sessions["pubchem-server"].call_tool("get_general_info_by_compound_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 FDA warnings result_2 = await sessions["fda-drug-server"].call_tool("get_warnings_and_cautions_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: Predict ADMET toxicity result_3 = await sessions["server-3"].call_tool("pred_molecule_admet", arguments={}) data_3 = parse(result_3) print(f"Step 3 result: {json.dumps(data_3, indent=2, ensure_ascii=False)[:500]}") # Step 4: Check structural alerts from ChEMBL result_4 = await sessions["chembl-server"].call_tool("get_compound_structural_alert", 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()) ```