Target Protein Retrieve
SkillSearchSearch the protein information from the input gene name and downloads the optimal PDB or AlphaFold structures.
Available today. Use it from your connected AI after setup.
No other account needed.
Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the Target Protein Retrieve skill
What this skill tells your AI
The instructions your AI receives, as published by internscience/scp in skills/drugsda-target-retrieve/SKILL.md and read by ahel’s review.
Usage
1. MCP Server Definition
import json
from mcp.client.streamable_http import streamablehttp_client
from mcp import ClientSession
class DrugSDAClient:
def __init__(self, server_url: str):
self.server_url = server_url
self.session = None
async def connect(self):
print(f"server url: {self.server_url}")
try:
self.transport = streamablehttp_client(
url=self.server_url,
headers={"SCP-HUB-API-KEY": "sk-a0033dde-b3cd-413b-adbe-980bc78d6126"}
)
self.read, self.write, self.get_session_id = await self.transport.__aenter__()
self.session_ctx = ClientSession(self.read, self.write)
self.session = await self.session_ctx.__aenter__()
await self.session.initialize()
session_id = self.get_session_id()
print(f"✓ connect success")
return True
except Exception as e:
print(f"✗ connect failure: {e}")
import traceback
traceback.print_exc()
return False
async def disconnect(self):
try:
if self.session:
await self.session_ctx.__aexit__(None, None, None)
if hasattr(self, 'transport'):
await self.transport.__aexit__(None, None, None)
print("✓ already disconnect")
except Exception as e:
print(f"✗ disconnect error: {e}")
def parse_result(self, result):
try:
if hasattr(result, 'content') and result.content:
content = result.content[0]
if hasattr(content, 'text'):
return json.loads(content.text)
return str(result)
except Exception as e:
return {"error": f"parse error: {e}", "raw": str(result)}
2. Retrieve Protein Structure
The description of tool retrieve_protein_structure_by_gene_name.
Search the protein information from the input gene name and downloads the optimal PDB or AlphaFold structures. Note that species support is limited to humans only.
Args:
gene_name (str): Input gene name (e.g., 'TP53')
Return:
status (str): success/error
msg (str): message
prot_structure_path (str): Path to the downloaded protein structure file (pdb format)
How to use tool retrieve_protein_structure_by_gene_name :
client = DrugSDAClient("https://scp.intern-ai.org.cn/api/v1/mcp/2/DrugSDA-Tool")
if not await client.connect():
print("connection failed")
return
response = await client.session.call_tool(
"retrieve_protein_structure_by_gene_name",
arguments={
"gene_name": gene_name
}
)
result = client.parse_result(response)
prot_structure_path = result["prot_structure_path"]
await client.disconnect()
Signals
- GitHub stars
- 167
- Forks
- 9
- Last commit
- Jun 2026
Advanced
- Catalog kind
- skill
- Gateway key
drugsda-target-retrieve- Source
- github.com/internscience/scp