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).
Discipline: Taxonomy | Tools Used: 4 | Servers: 3
Classify organism: NCBI taxonomy, Ensembl taxonomy, ChEMBL organisms, and genome info.
get_taxonomy from ncbi-server (streamable-http) - https://scp.intern-ai.org.cn/api/v1/mcp/9/Origene-NCBIget_taxonomy_id from ensembl-server (streamable-http) - https://scp.intern-ai.org.cn/api/v1/mcp/12/Origene-Ensemblget_organism_by_id from chembl-server (streamable-http) - https://scp.intern-ai.org.cn/api/v1/mcp/4/Origene-ChEMBLget_genome_dataset_report_by_taxon from ncbi-server (streamable-http) - https://scp.intern-ai.org.cn/api/v1/mcp/9/Origene-NCBI{
"taxon": "9606",
"species": "homo_sapiens"
}
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 = {
"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, 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["ncbi-server"] = await connect("https://scp.intern-ai.org.cn/api/v1/mcp/9/Origene-NCBI", stack)
sessions["ensembl-server"] = await connect("https://scp.intern-ai.org.cn/api/v1/mcp/12/Origene-Ensembl", stack)
sessions["chembl-server"] = await connect("https://scp.intern-ai.org.cn/api/v1/mcp/4/Origene-ChEMBL", stack)
# 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())