cancer_therapy_design
community[skill]
Cancer Therapy Design - Design cancer therapy: identify targets, find drugs, check safety, and analyze differential expression. Use this skill for oncology tasks involving get associated targets by disease efoId get associated drugs by target name get adverse reactions by drug name tcga differential expression analysis. Combines 4 tools from 3 SCP server(s).
$
/plugin install InnoClawdetails
Cancer Therapy Design
Discipline: Oncology | Tools Used: 4 | Servers: 3
Description
Design cancer therapy: identify targets, find drugs, check safety, and analyze differential expression.
Tools Used
get_associated_targets_by_disease_efoIdfromopentargets-server(streamable-http) -https://scp.intern-ai.org.cn/api/v1/mcp/15/Origene-OpenTargetsget_associated_drugs_by_target_namefromopentargets-server(streamable-http) -https://scp.intern-ai.org.cn/api/v1/mcp/15/Origene-OpenTargetsget_adverse_reactions_by_drug_namefromfda-drug-server(streamable-http) -https://scp.intern-ai.org.cn/api/v1/mcp/14/Origene-FDADrugtcga_differential_expression_analysisfromtcga-server(streamable-http) -https://scp.intern-ai.org.cn/api/v1/mcp/11/Origene-TCGA
Workflow
- Find cancer targets
- Get associated drugs
- Check drug safety
- Analyze differential expression
Test Case
Input
{
"disease_efo": "EFO_0000311",
"query": "lung adenocarcinoma drug targets"
}
Expected Steps
- Find cancer targets
- Get associated drugs
- Check drug safety
- Analyze differential expression
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 = {
"opentargets-server": "https://scp.intern-ai.org.cn/api/v1/mcp/15/Origene-OpenTargets",
"fda-drug-server": "https://scp.intern-ai.org.cn/api/v1/mcp/14/Origene-FDADrug",
"tcga-server": "https://scp.intern-ai.org.cn/api/v1/mcp/11/Origene-TCGA"
}
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["opentargets-server"] = await connect("https://scp.intern-ai.org.cn/api/v1/mcp/15/Origene-OpenTargets", stack)
sessions["fda-drug-server"] = await connect("https://scp.intern-ai.org.cn/api/v1/mcp/14/Origene-FDADrug", stack)
sessions["tcga-server"] = await connect("https://scp.intern-ai.org.cn/api/v1/mcp/11/Origene-TCGA", stack)
# Execute workflow steps
# Step 1: Find cancer targets
result_1 = await sessions["opentargets-server"].call_tool("get_associated_targets_by_disease_efoId", arguments={})
data_1 = parse(result_1)
print(f"Step 1 result: {json.dumps(data_1, indent=2, ensure_ascii=False)[:500]}")
# Step 2: Get associated drugs
result_2 = await sessions["opentargets-server"].call_tool("get_associated_drugs_by_target_name", arguments={})
data_2 = parse(result_2)
print(f"Step 2 result: {json.dumps(data_2, indent=2, ensure_ascii=False)[:500]}")
# Step 3: Check drug safety
result_3 = await sessions["fda-drug-server"].call_tool("get_adverse_reactions_by_drug_name", arguments={})
data_3 = parse(result_3)
print(f"Step 3 result: {json.dumps(data_3, indent=2, ensure_ascii=False)[:500]}")
# Step 4: Analyze differential expression
result_4 = await sessions["tcga-server"].call_tool("tcga_differential_expression_analysis", 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/cancer_therapy_design/SKILL.md