Pharmacogenomics Analysis
SkillSearchPharmacogenomics Analysis - Pharmacogenomics analysis: FDA pharmacogenomics info, variant effects, ClinVar pathogenicity, and gene expression. Use this skill for pharmacogenomics tasks involving get pharmacogenomics info by drug name get vep hgvs clinvar search get gene expression across cancers. Combines 4 tools from 4 SCP server(s).
Available today. Use it from your connected AI after setup.
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Then ask your AI: use the Pharmacogenomics Analysis skill
What this skill tells your AI
The instructions your AI receives, as published by internscience/scp in skills/pharmacogenomics_analysis/SKILL.md and read by ahel’s review.
Discipline: Pharmacogenomics | Tools Used: 4 | Servers: 4
Description
Pharmacogenomics analysis: FDA pharmacogenomics info, variant effects, ClinVar pathogenicity, and gene expression.
Tools Used
get_pharmacogenomics_info_by_drug_namefromfda-drug-server(streamable-http) -https://scp.intern-ai.org.cn/api/v1/mcp/14/Origene-FDADrugget_vep_hgvsfromensembl-server(streamable-http) -https://scp.intern-ai.org.cn/api/v1/mcp/12/Origene-Ensemblclinvar_searchfromsearch-server(streamable-http) -https://scp.intern-ai.org.cn/api/v1/mcp/7/Origene-Searchget_gene_expression_across_cancersfromtcga-server(streamable-http) -https://scp.intern-ai.org.cn/api/v1/mcp/11/Origene-TCGA
Workflow
- Get FDA pharmacogenomics info
- Predict effect of CYP2C9 variants
- Search ClinVar for CYP2C9 variants
- Check CYP2C9 expression across cancers
Test Case
Input
{
"drug_name": "warfarin",
"gene": "CYP2C9"
}
Expected Steps
- Get FDA pharmacogenomics info
- Predict effect of CYP2C9 variants
- Search ClinVar for CYP2C9 variants
- Check CYP2C9 expression across cancers
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 = {
"fda-drug-server": "https://scp.intern-ai.org.cn/api/v1/mcp/14/Origene-FDADrug",
"ensembl-server": "https://scp.intern-ai.org.cn/api/v1/mcp/12/Origene-Ensembl",
"search-server": "https://scp.intern-ai.org.cn/api/v1/mcp/7/Origene-Search",
"tcga-server": "https://scp.intern-ai.org.cn/api/v1/mcp/11/Origene-TCGA"
}
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():
# Connect to required servers
sessions = {}
sessions["fda-drug-server"], _, _ = await connect("https://scp.intern-ai.org.cn/api/v1/mcp/14/Origene-FDADrug", "streamable-http")
sessions["ensembl-server"], _, _ = await connect("https://scp.intern-ai.org.cn/api/v1/mcp/12/Origene-Ensembl", "streamable-http")
sessions["search-server"], _, _ = await connect("https://scp.intern-ai.org.cn/api/v1/mcp/7/Origene-Search", "streamable-http")
sessions["tcga-server"], _, _ = await connect("https://scp.intern-ai.org.cn/api/v1/mcp/11/Origene-TCGA", "streamable-http")
# Execute workflow steps
# Step 1: Get FDA pharmacogenomics info
result_1 = await sessions["fda-drug-server"].call_tool("get_pharmacogenomics_info_by_drug_name", arguments={})
data_1 = parse(result_1)
print(f"Step 1 result: {json.dumps(data_1, indent=2, ensure_ascii=False)[:500]}")
# Step 2: Predict effect of CYP2C9 variants
result_2 = await sessions["ensembl-server"].call_tool("get_vep_hgvs", arguments={})
data_2 = parse(result_2)
print(f"Step 2 result: {json.dumps(data_2, indent=2, ensure_ascii=False)[:500]}")
# Step 3: Search ClinVar for CYP2C9 variants
result_3 = await sessions["search-server"].call_tool("clinvar_search", arguments={})
data_3 = parse(result_3)
print(f"Step 3 result: {json.dumps(data_3, indent=2, ensure_ascii=False)[:500]}")
# Step 4: Check CYP2C9 expression across cancers
result_4 = await sessions["tcga-server"].call_tool("get_gene_expression_across_cancers", 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())
Signals
- GitHub stars
- 167
- Forks
- 9
- Last commit
- Jun 2026
Advanced
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- skill
- Gateway key
pharmacogenomics-analysis- Source
- github.com/internscience/scp