name: gene_family_evolution description: "Gene Family Evolution Analysis - Analyze gene family evolution: CAFE gene tree, homology, Ensembl gene tree, and taxonomy. Use this skill for molecular evolution tasks involving get cafe genetree member symbol get homology symbol get genetree member symbol get taxonomy classification. Combines 4 tools from 1 SCP server(s)."
Gene Family Evolution Analysis
Discipline: Molecular Evolution | Tools Used: 4 | Servers: 1
Description
Analyze gene family evolution: CAFE gene tree, homology, Ensembl gene tree, and taxonomy.
Tools Used
get_cafe_genetree_member_symbolfromensembl-server(streamable-http) -https://scp.intern-ai.org.cn/api/v1/mcp/12/Origene-Ensemblget_homology_symbolfromensembl-server(streamable-http) -https://scp.intern-ai.org.cn/api/v1/mcp/12/Origene-Ensemblget_genetree_member_symbolfromensembl-server(streamable-http) -https://scp.intern-ai.org.cn/api/v1/mcp/12/Origene-Ensemblget_taxonomy_classificationfromensembl-server(streamable-http) -https://scp.intern-ai.org.cn/api/v1/mcp/12/Origene-Ensembl
Workflow
- Get CAFE gene family evolution tree
- Find homologs across species
- Get full gene tree
- Get taxonomic classification
Test Case
Input
{
"gene": "TP53",
"species": "homo_sapiens"
}
Expected Steps
- Get CAFE gene family evolution tree
- Find homologs across species
- Get full gene tree
- Get taxonomic classification
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 = {
"ensembl-server": "https://scp.intern-ai.org.cn/api/v1/mcp/12/Origene-Ensembl"
}
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")
# Execute workflow steps
# Step 1: Get CAFE gene family evolution tree
result_1 = await sessions["ensembl-server"].call_tool("get_cafe_genetree_member_symbol", arguments={})
data_1 = parse(result_1)
print(f"Step 1 result: {json.dumps(data_1, indent=2, ensure_ascii=False)[:500]}")
# Step 2: Find homologs across species
result_2 = await sessions["ensembl-server"].call_tool("get_homology_symbol", arguments={})
data_2 = parse(result_2)
print(f"Step 2 result: {json.dumps(data_2, indent=2, ensure_ascii=False)[:500]}")
# Step 3: Get full gene tree
result_3 = await sessions["ensembl-server"].call_tool("get_genetree_member_symbol", arguments={})
data_3 = parse(result_3)
print(f"Step 3 result: {json.dumps(data_3, indent=2, ensure_ascii=False)[:500]}")
# Step 4: Get taxonomic classification
result_4 = await sessions["ensembl-server"].call_tool("get_taxonomy_classification", 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())