Skill Index

InnoClaw/

protein_complex_analysis

community[skill]

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).

$/plugin install InnoClaw

details

Protein Complex Visualization & Analysis

Discipline: Structural Biology | Tools Used: 4 | Servers: 1

Description

Analyze protein complex: download structure, visualize complex, extract chains, and calculate quality metrics.

Tools Used

  • retrieve_protein_data_by_pdbcode from server-2 (streamable-http) - https://scp.intern-ai.org.cn/api/v1/mcp/2/DrugSDA-Tool
  • visualize_complex from server-2 (streamable-http) - https://scp.intern-ai.org.cn/api/v1/mcp/2/DrugSDA-Tool
  • extract_pdb_chains from server-2 (streamable-http) - https://scp.intern-ai.org.cn/api/v1/mcp/2/DrugSDA-Tool
  • calculate_pdb_basic_info from server-2 (streamable-http) - https://scp.intern-ai.org.cn/api/v1/mcp/2/DrugSDA-Tool

Workflow

  1. Download complex structure
  2. Visualize protein-ligand complex
  3. Extract individual chains
  4. Calculate structural statistics

Test Case

Input

{
    "pdb_code": "6LU7"
}

Expected Steps

  1. Download complex structure
  2. Visualize protein-ligand complex
  3. Extract individual chains
  4. Calculate structural statistics

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.

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())

technical

github
SpectrAI-Initiative/InnoClaw
stars
374
license
Apache-2.0
contributors
16
last commit
2026-04-20T01:27:21Z
file
.claude/skills/protein_complex_analysis/SKILL.md

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