.claude/skills/gene_family_evolution/SKILL.md
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).
npx skillsauth add SpectrAI-Initiative/InnoClaw gene_family_evolutionInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Discipline: Molecular Evolution | Tools Used: 4 | Servers: 1
Analyze gene family evolution: CAFE gene tree, homology, Ensembl gene tree, and taxonomy.
get_cafe_genetree_member_symbol from ensembl-server (streamable-http) - https://scp.intern-ai.org.cn/api/v1/mcp/12/Origene-Ensemblget_homology_symbol from ensembl-server (streamable-http) - https://scp.intern-ai.org.cn/api/v1/mcp/12/Origene-Ensemblget_genetree_member_symbol from ensembl-server (streamable-http) - https://scp.intern-ai.org.cn/api/v1/mcp/12/Origene-Ensemblget_taxonomy_classification from ensembl-server (streamable-http) - https://scp.intern-ai.org.cn/api/v1/mcp/12/Origene-Ensembl{
"gene": "TP53",
"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 = {
"ensembl-server": "https://scp.intern-ai.org.cn/api/v1/mcp/12/Origene-Ensembl"
}
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["ensembl-server"] = await connect("https://scp.intern-ai.org.cn/api/v1/mcp/12/Origene-Ensembl", stack)
# 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())
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