.claude/skills/protein_complex_analysis/SKILL.md
Protein Complex Visualization & Analysis - Analyze protein complex: download structure, visualize complex, extract chains, and calculate quality metrics. Use this skill for structural biology tasks involving retrieve protein data by pdbcode visualize complex extract pdb chains calculate pdb basic info. Combines 4 tools from 1 SCP server(s).
npx skillsauth add SpectrAI-Initiative/InnoClaw protein_complex_analysisInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
3 of 9 scanners reported clean
Some scanners were skipped, did not run, or reported a non-clean status. Review each row below.
Discipline: Structural Biology | Tools Used: 4 | Servers: 1
Analyze protein complex: download structure, visualize complex, extract chains, and calculate quality metrics.
retrieve_protein_data_by_pdbcode from server-2 (streamable-http) - https://scp.intern-ai.org.cn/api/v1/mcp/2/DrugSDA-Toolvisualize_complex from server-2 (streamable-http) - https://scp.intern-ai.org.cn/api/v1/mcp/2/DrugSDA-Toolextract_pdb_chains from server-2 (streamable-http) - https://scp.intern-ai.org.cn/api/v1/mcp/2/DrugSDA-Toolcalculate_pdb_basic_info from server-2 (streamable-http) - https://scp.intern-ai.org.cn/api/v1/mcp/2/DrugSDA-Tool{
"pdb_code": "6LU7"
}
Note: Replace
sk-b04409a1-b32b-4511-9aeb-22980abdc05cwith your own SCP Hub API Key. You can obtain one from the SCP Platform.
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 = {
"server-2": "https://scp.intern-ai.org.cn/api/v1/mcp/2/DrugSDA-Tool"
}
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["server-2"] = await connect("https://scp.intern-ai.org.cn/api/v1/mcp/2/DrugSDA-Tool", stack)
# Execute workflow steps
# Step 1: Download complex structure
result_1 = await sessions["server-2"].call_tool("retrieve_protein_data_by_pdbcode", arguments={})
data_1 = parse(result_1)
print(f"Step 1 result: {json.dumps(data_1, indent=2, ensure_ascii=False)[:500]}")
# Step 2: Visualize protein-ligand complex
result_2 = await sessions["server-2"].call_tool("visualize_complex", arguments={})
data_2 = parse(result_2)
print(f"Step 2 result: {json.dumps(data_2, indent=2, ensure_ascii=False)[:500]}")
# Step 3: Extract individual chains
result_3 = await sessions["server-2"].call_tool("extract_pdb_chains", arguments={})
data_3 = parse(result_3)
print(f"Step 3 result: {json.dumps(data_3, indent=2, ensure_ascii=False)[:500]}")
# Step 4: Calculate structural statistics
result_4 = await sessions["server-2"].call_tool("calculate_pdb_basic_info", 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())
tools
Use the local InnoClaw CLI to run app workflows and Deep Research sessions from the terminal. Trigger when the user wants command-line control over this repository instead of only using the web UI.
tools
SNP Functional Impact Analysis - Analyze SNP function: VEP prediction, variation details, phenotype association, and literature evidence. Use this skill for functional genomics tasks involving get vep id get variation get phenotype accession pubmed search. Combines 4 tools from 2 SCP server(s).
tools
SMILES Comprehensive Analysis - Comprehensive SMILES analysis: validate, convert name, compute all molecular descriptors, and predict ADMET. Use this skill for cheminformatics tasks involving is valid smiles ChemicalStructureAnalyzer calculate mol basic info pred molecule admet. Combines 4 tools from 3 SCP server(s).
tools
Convert SMILES strings to CAS registry numbers using material informatics tools to identify chemical substances.