blast-protein-analysis

name	blast_protein_analysis
description	BLAST & Protein Analysis Pipeline - BLAST search followed by comprehensive protein analysis: BLAST, then structure prediction, properties, and function. Use this skill for sequence bioinformatics tasks involving blast search pred protein structure esmfold calculate protein sequence properties predict protein function. Combines 4 tools from 4 SCP server(s).
i18n	{"zh":{"description":"BLAST与蛋白质分析流程。"}}

BLAST & Protein Analysis Pipeline

Discipline: Sequence Bioinformatics | Tools Used: 4 | Servers: 4

Description

BLAST search followed by comprehensive protein analysis: BLAST, then structure prediction, properties, and function.

Tools Used

• blast_search from server-17 (streamable-http) - https://scp.intern-ai.org.cn/api/v1/mcp/17/BioInfo-Tools
• pred_protein_structure_esmfold from server-3 (streamable-http) - https://scp.intern-ai.org.cn/api/v1/mcp/3/DrugSDA-Model
• calculate_protein_sequence_properties from server-2 (streamable-http) - https://scp.intern-ai.org.cn/api/v1/mcp/2/DrugSDA-Tool
• predict_protein_function from server-1 (sse) - https://scp.intern-ai.org.cn/api/v1/mcp/1/VenusFactory

Workflow

1. Run BLAST search
2. Predict structure for top hit
3. Calculate protein properties
4. Predict protein function

Test Case

Input

{
    "sequence": "MKTIIALSYIFCLVFA"
}

Expected Steps

1. Run BLAST search
2. Predict structure for top hit
3. Calculate protein properties
4. Predict protein function

Usage Example

Note: Replace <YOUR_SCP_HUB_API_KEY> with your own SCP Hub API Key. You can obtain one from the SCP Platform.

import asyncio
import json
from mcp import ClientSession
from mcp.client.streamable_http import streamablehttp_client
from mcp.client.sse import sse_client

SERVERS = {
    "server-17": "https://scp.intern-ai.org.cn/api/v1/mcp/17/BioInfo-Tools",
    "server-3": "https://scp.intern-ai.org.cn/api/v1/mcp/3/DrugSDA-Model",
    "server-2": "https://scp.intern-ai.org.cn/api/v1/mcp/2/DrugSDA-Tool",
    "server-1": "https://scp.intern-ai.org.cn/api/v1/mcp/1/VenusFactory"
}

async def connect(url, transport_type):
    transport = streamablehttp_client(url=url, headers={"SCP-HUB-API-KEY": "<YOUR_SCP_HUB_API_KEY>"})
    read, write, _ = await transport.__aenter__()
    ctx = ClientSession(read, write)
    session = await ctx.__aenter__()
    await session.initialize()
    return session, ctx, transport

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)
    :  (result)

  ():
    
    sessions = {}
    sessions[], _, _ =  connect(, )
    sessions[], _, _ =  connect(, )
    sessions[], _, _ =  connect(, )
    sessions[], _, _ =  connect(, )

    
    
    result_1 =  sessions[].call_tool(, arguments={})
    data_1 = parse(result_1)
    ()

    
    result_2 =  sessions[].call_tool(, arguments={})
    data_2 = parse(result_2)
    ()

    
    result_3 =  sessions[].call_tool(, arguments={})
    data_3 = parse(result_3)
    ()

    
    result_4 =  sessions[].call_tool(, arguments={})
    data_4 = parse(result_4)
    ()

    
    ()

 __name__ == :
    asyncio.run(main())