biosample_genomics
$
npx mdskill add InternScience/scp/biosample_genomicsCross-reference biosample and genome data from NCBI using multiple reports
- Solve genomics tasks by retrieving biosample and genome reports
- Uses NCBI APIs for biosample, genome dataset, sequence, and taxonomy data
- Automatically selects and executes required tools based on input parameters
- Returns consolidated reports and data in structured JSON format
SKILL.md
.github/skills/biosample_genomicsView on GitHub ↗
---
name: biosample_genomics
description: "BioSample & Genome Cross-Reference - Cross-reference biosample and genome data: NCBI biosample, genome report, sequence reports, and taxonomy. Use this skill for genomics tasks involving get biosample report get genome dataset report by accession get genome sequence reports get taxonomy. Combines 4 tools from 1 SCP server(s)."
---
# BioSample & Genome Cross-Reference
**Discipline**: Genomics | **Tools Used**: 4 | **Servers**: 1
## Description
Cross-reference biosample and genome data: NCBI biosample, genome report, sequence reports, and taxonomy.
## Tools Used
- **`get_biosample_report`** from `ncbi-server` (streamable-http) - `https://scp.intern-ai.org.cn/api/v1/mcp/9/Origene-NCBI`
- **`get_genome_dataset_report_by_accession`** from `ncbi-server` (streamable-http) - `https://scp.intern-ai.org.cn/api/v1/mcp/9/Origene-NCBI`
- **`get_genome_sequence_reports`** from `ncbi-server` (streamable-http) - `https://scp.intern-ai.org.cn/api/v1/mcp/9/Origene-NCBI`
- **`get_taxonomy`** from `ncbi-server` (streamable-http) - `https://scp.intern-ai.org.cn/api/v1/mcp/9/Origene-NCBI`
## Workflow
1. Get biosample report
2. Get genome dataset report
3. Get sequence reports
4. Get taxonomy
## Test Case
### Input
```json
{
"biosample": "SAMN15795254",
"genome_accession": "GCF_000001405.40"
}
```
### Expected Steps
1. Get biosample report
2. Get genome dataset report
3. Get sequence reports
4. Get taxonomy
## 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 = {
"ncbi-server": "https://scp.intern-ai.org.cn/api/v1/mcp/9/Origene-NCBI"
}
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["ncbi-server"], _, _ = await connect("https://scp.intern-ai.org.cn/api/v1/mcp/9/Origene-NCBI", "streamable-http")
# Execute workflow steps
# Step 1: Get biosample report
result_1 = await sessions["ncbi-server"].call_tool("get_biosample_report", arguments={})
data_1 = parse(result_1)
print(f"Step 1 result: {json.dumps(data_1, indent=2, ensure_ascii=False)[:500]}")
# Step 2: Get genome dataset report
result_2 = await sessions["ncbi-server"].call_tool("get_genome_dataset_report_by_accession", arguments={})
data_2 = parse(result_2)
print(f"Step 2 result: {json.dumps(data_2, indent=2, ensure_ascii=False)[:500]}")
# Step 3: Get sequence reports
result_3 = await sessions["ncbi-server"].call_tool("get_genome_sequence_reports", arguments={})
data_3 = parse(result_3)
print(f"Step 3 result: {json.dumps(data_3, indent=2, ensure_ascii=False)[:500]}")
# Step 4: Get taxonomy
result_4 = await sessions["ncbi-server"].call_tool("get_taxonomy", 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())
```