synthetic_biology_design
community[skill]
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).
$
/plugin install InnoClawdetails
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_idfromensembl-server(streamable-http) -https://scp.intern-ai.org.cn/api/v1/mcp/12/Origene-EnsemblDegenerateCodonCalculatorbyAminoAcidfromserver-29(sse) -https://scp.intern-ai.org.cn/api/v1/mcp/29/SciToolAgent-Biocalculate_protein_sequence_propertiesfromserver-2(streamable-http) -https://scp.intern-ai.org.cn/api/v1/mcp/2/DrugSDA-Toolpred_protein_structure_esmfoldfromserver-3(streamable-http) -https://scp.intern-ai.org.cn/api/v1/mcp/3/DrugSDA-Model
Workflow
- Get gene sequence
- Design degenerate codons
- Predict protein properties
- Predict structure
Test Case
Input
{
"gene_id": "ENSG00000141510",
"amino_acids": "AVILM"
}
Expected Steps
- Get gene sequence
- Design degenerate codons
- Predict protein properties
- Predict structure
Usage Example
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 = {
"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: return c.text
return str(result)
except: return str(result)
async def main():
async with AsyncExitStack() as stack:
# Connect to required servers
sessions = {}
sessions["ensembl-server"] = await connect("https://scp.intern-ai.org.cn/api/v1/mcp/12/Origene-Ensembl", stack)
sessions["server-29"] = await connect("https://scp.intern-ai.org.cn/api/v1/mcp/29/SciToolAgent-Bio", stack)
sessions["server-2"] = await connect("https://scp.intern-ai.org.cn/api/v1/mcp/2/DrugSDA-Tool", stack)
sessions["server-3"] = await connect("https://scp.intern-ai.org.cn/api/v1/mcp/3/DrugSDA-Model", stack)
# Execute workflow steps
# Step 1: Get gene sequence
result_1 = await sessions["ensembl-server"].call_tool("get_sequence_id", arguments={})
data_1 = parse(result_1)
print(f"Step 1 result: {json.dumps(data_1, indent=2, ensure_ascii=False)[:500]}")
# Step 2: Design degenerate codons
result_2 = await sessions["server-29"].call_tool("DegenerateCodonCalculatorbyAminoAcid", arguments={})
data_2 = parse(result_2)
print(f"Step 2 result: {json.dumps(data_2, indent=2, ensure_ascii=False)[:500]}")
# Step 3: Predict protein properties
result_3 = await sessions["server-2"].call_tool("calculate_protein_sequence_properties", arguments={})
data_3 = parse(result_3)
print(f"Step 3 result: {json.dumps(data_3, indent=2, ensure_ascii=False)[:500]}")
# Step 4: Predict structure
result_4 = await sessions["server-3"].call_tool("pred_protein_structure_esmfold", 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/synthetic_biology_design/SKILL.md