chemical_safety_assessment

# 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_...