genetic_counseling_report
$
npx mdskill add InternScience/scp/genetic_counseling_report**Discipline**: Clinical Genetics | **Tools Used**: 4 | **Servers**: 2
SKILL.md
.github/skills/genetic_counseling_reportView on GitHub ↗
---
name: genetic_counseling_report
description: "Genetic Counseling Variant Report - Generate variant report for genetic counseling: VEP, ClinVar, gene phenotype, and literature evidence. Use this skill for clinical genetics tasks involving get vep hgvs clinvar search get phenotype gene pubmed search. Combines 4 tools from 2 SCP server(s)."
---
# Genetic Counseling Variant Report
**Discipline**: Clinical Genetics | **Tools Used**: 4 | **Servers**: 2
## Description
Generate variant report for genetic counseling: VEP, ClinVar, gene phenotype, and literature evidence.
## Tools Used
- **`get_vep_hgvs`** from `ensembl-server` (streamable-http) - `https://scp.intern-ai.org.cn/api/v1/mcp/12/Origene-Ensembl`
- **`clinvar_search`** from `search-server` (streamable-http) - `https://scp.intern-ai.org.cn/api/v1/mcp/7/Origene-Search`
- **`get_phenotype_gene`** from `ensembl-server` (streamable-http) - `https://scp.intern-ai.org.cn/api/v1/mcp/12/Origene-Ensembl`
- **`pubmed_search`** from `search-server` (streamable-http) - `https://scp.intern-ai.org.cn/api/v1/mcp/7/Origene-Search`
## Workflow
1. Predict variant effect with VEP
2. Search ClinVar significance
3. Get gene-phenotype associations
4. Search PubMed for clinical evidence
## Test Case
### Input
```json
{
"hgvs": "ENSP00000269305.4:p.Arg175His",
"gene": "TP53"
}
```
### Expected Steps
1. Predict variant effect with VEP
2. Search ClinVar significance
3. Get gene-phenotype associations
4. Search PubMed for clinical evidence
## Usage Example
> **Note:** Replace `<YOUR_SCP_HUB_API_KEY>` with your own SCP Hub API Key. You can obtain one from the [SCP Platform](https://scphub.intern-ai.org.cn).
```python
import asyncio
import json
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",
"search-server": "https://scp.intern-ai.org.cn/api/v1/mcp/7/Origene-Search"
}
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["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")
# Execute workflow steps
# Step 1: Predict variant effect with VEP
result_1 = await sessions["ensembl-server"].call_tool("get_vep_hgvs", arguments={})
data_1 = parse(result_1)
print(f"Step 1 result: {json.dumps(data_1, indent=2, ensure_ascii=False)[:500]}")
# Step 2: Search ClinVar significance
result_2 = await sessions["search-server"].call_tool("clinvar_search", arguments={})
data_2 = parse(result_2)
print(f"Step 2 result: {json.dumps(data_2, indent=2, ensure_ascii=False)[:500]}")
# Step 3: Get gene-phenotype associations
result_3 = await sessions["ensembl-server"].call_tool("get_phenotype_gene", arguments={})
data_3 = parse(result_3)
print(f"Step 3 result: {json.dumps(data_3, indent=2, ensure_ascii=False)[:500]}")
# Step 4: Search PubMed for clinical evidence
result_4 = await sessions["search-server"].call_tool("pubmed_search", 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())
```