synthetic-biology-design

name	synthetic_biology_design
description	Synthetic Biology Design - Design synthetic biology construct: gene lookup, codon optimization, protein property prediction, and structure prediction. Use this skill for synthetic biology tasks involving get sequence id DegenerateCodonCalculatorbyAminoAcid calculate protein sequence properties pred protein structure esmfold. Combines 4 tools from 4 SCP server(s).

Synthetic Biology Design

Discipline: Synthetic Biology | Tools Used: 4 | Servers: 4

Description

Design synthetic biology construct: gene lookup, codon optimization, protein property prediction, and structure prediction.

Tools Used

• get_sequence_id from ensembl-server (streamable-http) - https://scp.intern-ai.org.cn/api/v1/mcp/12/Origene-Ensembl
• DegenerateCodonCalculatorbyAminoAcid from server-29 (sse) - https://scp.intern-ai.org.cn/api/v1/mcp/29/SciToolAgent-Bio
• calculate_protein_sequence_properties from server-2 (streamable-http) - https://scp.intern-ai.org.cn/api/v1/mcp/2/DrugSDA-Tool
• pred_protein_structure_esmfold from server-3 (streamable-http) - https://scp.intern-ai.org.cn/api/v1/mcp/3/DrugSDA-Model

Workflow

1. Get gene sequence
2. Design degenerate codons
3. Predict protein properties
4. Predict structure

Test Case

Input

{
    "gene_id": "ENSG00000141510",
    "amino_acids": "AVILM"
}

Expected Steps

1. Get gene sequence
2. Design degenerate codons
3. Predict protein properties
4. Predict structure

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 = {
    "ensembl-server": "https://scp.intern-ai.org.cn/api/v1/mcp/12/Origene-Ensembl",
    "server-29": "https://scp.intern-ai.org.cn/api/v1/mcp/29/SciToolAgent-Bio",
    "server-2": "https://scp.intern-ai.org.cn/api/v1/mcp/2/DrugSDA-Tool",
    "server-3": "https://scp.intern-ai.org.cn/api/v1/mcp/3/DrugSDA-Model"
}

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:  c.text
         (result)
    :  (result)

  ():
      AsyncExitStack()  stack:
        
        sessions = {}
        sessions[] =  connect(, stack)
        sessions[] =  connect(, stack)
        sessions[] =  connect(, stack)
        sessions[] =  connect(, stack)

        
        
        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())