| name | mouse_model_analysis |
| description | Mouse Model Disease Analysis - Analyze mouse disease models: MouseMine search, NCBI mouse gene data, Ensembl cross-species comparison, and orthologs. Use this skill for model organisms tasks involving mousemine search get gene metadata by gene name get homology symbol get gene orthologs. Combines 4 tools from 3 SCP server(s). |
Mouse Model Disease Analysis
Discipline: Model Organisms | Tools Used: 4 | Servers: 3
Description
Analyze mouse disease models: MouseMine search, NCBI mouse gene data, Ensembl cross-species comparison, and orthologs.
Tools Used
mousemine_search from search-server (streamable-http) - https://scp.intern-ai.org.cn/api/v1/mcp/7/Origene-Search
get_gene_metadata_by_gene_name from ncbi-server (streamable-http) - https://scp.intern-ai.org.cn/api/v1/mcp/9/Origene-NCBI
get_homology_symbol from ensembl-server (streamable-http) - https://scp.intern-ai.org.cn/api/v1/mcp/12/Origene-Ensembl
get_gene_orthologs from ncbi-server (streamable-http) - https://scp.intern-ai.org.cn/api/v1/mcp/9/Origene-NCBI
Workflow
- Search MouseMine
- Get mouse gene data
- Find human-mouse homologs
- Get gene orthologs
Test Case
Input
{
"query": "Trp53 tumor mouse model",
"gene": "TP53"
}
Expected Steps
- Search MouseMine
- Get mouse gene data
- Find human-mouse homologs
- Get gene orthologs
Usage Example
Note: Replace sk-b04409a1-b32b-4511-9aeb-22980abdc05c with 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 = {
"search-server": "https://scp.intern-ai.org.cn/api/v1/mcp/7/Origene-Search",
"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"
}
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)
: (result)
():
AsyncExitStack() stack:
sessions = {}
sessions[] = connect(, stack)
sessions[] = connect(, stack)
sessions[] = connect(, stack)
result_1 = sessions[].call_tool(, arguments={})
data_1 = parse(result_1)
()
result_2 = sessions[].call_tool(, arguments={})
data_2 = parse(result_2)
()
result_3 = sessions[].call_tool(, arguments={})
data_3 = parse(result_3)
()
result_4 = sessions[].call_tool(, arguments={})
data_4 = parse(result_4)
()
()
__name__ == :
asyncio.run(main())