| name | disease_protein_profiling |
| description | Disease Protein Profiling - Profile a disease protein: UniProt data, AlphaFold structure, InterPro domains, phenotype associations from Ensembl. Use this skill for medical proteomics tasks involving query uniprot download alphafold structure query interpro get phenotype gene. Combines 4 tools from 2 SCP server(s). |
| i18n | {"zh":{"description":"疾病蛋白分析:UniProt、。"}} |
Disease Protein Profiling
Discipline: Medical Proteomics | Tools Used: 4 | Servers: 2
Description
Profile a disease protein: UniProt data, AlphaFold structure, InterPro domains, phenotype associations from Ensembl.
Tools Used
query_uniprot from server-1 (sse) - https://scp.intern-ai.org.cn/api/v1/mcp/1/VenusFactory
download_alphafold_structure from server-1 (sse) - https://scp.intern-ai.org.cn/api/v1/mcp/1/VenusFactory
query_interpro from server-1 (sse) - https://scp.intern-ai.org.cn/api/v1/mcp/1/VenusFactory
get_phenotype_gene from ensembl-server (streamable-http) - https://scp.intern-ai.org.cn/api/v1/mcp/12/Origene-Ensembl
Workflow
- Get UniProt protein data
- Download AlphaFold predicted structure
- Get InterPro domain info
- Get phenotype associations
Test Case
Input
{
"uniprot_id": "P04637",
"gene_symbol": "TP53",
"species": "homo_sapiens"
}
Expected Steps
- Get UniProt protein data
- Download AlphaFold predicted structure
- Get InterPro domain info
- Get phenotype associations
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-1": "https://scp.intern-ai.org.cn/api/v1/mcp/1/VenusFactory",
"ensembl-server": "https://scp.intern-ai.org.cn/api/v1/mcp/12/Origene-Ensembl"
}
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)
except: return str(result)
async def main():
sessions = {}
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())