organism_classification
$
npx mdskill add InternScience/scp/organism_classification**Discipline**: Taxonomy | **Tools Used**: 4 | **Servers**: 3
SKILL.md
.github/skills/organism_classificationView on GitHub ↗
---
name: organism_classification
description: "Organism Classification & Database - Classify organism: NCBI taxonomy, Ensembl taxonomy, ChEMBL organisms, and genome info. Use this skill for taxonomy tasks involving get taxonomy get taxonomy id get organism by id get genome dataset report by taxon. Combines 4 tools from 3 SCP server(s)."
---
# Organism Classification & Database
**Discipline**: Taxonomy | **Tools Used**: 4 | **Servers**: 3
## Description
Classify organism: NCBI taxonomy, Ensembl taxonomy, ChEMBL organisms, and genome info.
## Tools Used
- **`get_taxonomy`** from `ncbi-server` (streamable-http) - `https://scp.intern-ai.org.cn/api/v1/mcp/9/Origene-NCBI`
- **`get_taxonomy_id`** from `ensembl-server` (streamable-http) - `https://scp.intern-ai.org.cn/api/v1/mcp/12/Origene-Ensembl`
- **`get_organism_by_id`** from `chembl-server` (streamable-http) - `https://scp.intern-ai.org.cn/api/v1/mcp/4/Origene-ChEMBL`
- **`get_genome_dataset_report_by_taxon`** from `ncbi-server` (streamable-http) - `https://scp.intern-ai.org.cn/api/v1/mcp/9/Origene-NCBI`
## Workflow
1. Get NCBI taxonomy
2. Get Ensembl taxonomy
3. Get ChEMBL organism info
4. Get genome dataset report
## Test Case
### Input
```json
{
"taxon": "9606",
"species": "homo_sapiens"
}
```
### Expected Steps
1. Get NCBI taxonomy
2. Get Ensembl taxonomy
3. Get ChEMBL organism info
4. Get genome dataset report
## 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",
"ensembl-server": "https://scp.intern-ai.org.cn/api/v1/mcp/12/Origene-Ensembl",
"chembl-server": "https://scp.intern-ai.org.cn/api/v1/mcp/4/Origene-ChEMBL"
}
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")
sessions["ensembl-server"], _, _ = await connect("https://scp.intern-ai.org.cn/api/v1/mcp/12/Origene-Ensembl", "streamable-http")
sessions["chembl-server"], _, _ = await connect("https://scp.intern-ai.org.cn/api/v1/mcp/4/Origene-ChEMBL", "streamable-http")
# Execute workflow steps
# Step 1: Get NCBI taxonomy
result_1 = await sessions["ncbi-server"].call_tool("get_taxonomy", arguments={})
data_1 = parse(result_1)
print(f"Step 1 result: {json.dumps(data_1, indent=2, ensure_ascii=False)[:500]}")
# Step 2: Get Ensembl taxonomy
result_2 = await sessions["ensembl-server"].call_tool("get_taxonomy_id", arguments={})
data_2 = parse(result_2)
print(f"Step 2 result: {json.dumps(data_2, indent=2, ensure_ascii=False)[:500]}")
# Step 3: Get ChEMBL organism info
result_3 = await sessions["chembl-server"].call_tool("get_organism_by_id", arguments={})
data_3 = parse(result_3)
print(f"Step 3 result: {json.dumps(data_3, indent=2, ensure_ascii=False)[:500]}")
# Step 4: Get genome dataset report
result_4 = await sessions["ncbi-server"].call_tool("get_genome_dataset_report_by_taxon", 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())
```