snp-functional-analysis

name	snp_functional_analysis
description	SNP Functional Impact Analysis - Analyze SNP function: VEP prediction, variation details, phenotype association, and literature evidence. Use this skill for functional genomics tasks involving get vep id get variation get phenotype accession pubmed search. Combines 4 tools from 2 SCP server(s).
i18n	{"zh":{"description":"SNP功能影响分析。"}}

SNP Functional Impact Analysis

Discipline: Functional Genomics | Tools Used: 4 | Servers: 2

Description

Analyze SNP function: VEP prediction, variation details, phenotype association, and literature evidence.

Tools Used

• get_vep_id from ensembl-server (streamable-http) - https://scp.intern-ai.org.cn/api/v1/mcp/12/Origene-Ensembl
• get_variation from ensembl-server (streamable-http) - https://scp.intern-ai.org.cn/api/v1/mcp/12/Origene-Ensembl
• get_phenotype_accession from ensembl-server (streamable-http) - https://scp.intern-ai.org.cn/api/v1/mcp/12/Origene-Ensembl
• pubmed_search from search-server (streamable-http) - https://scp.intern-ai.org.cn/api/v1/mcp/7/Origene-Search

Workflow

1. Predict functional effects with VEP
2. Get variant details
3. Get phenotype associations
4. Search PubMed for evidence

Test Case

Input

{
    "variant_id": "rs1800497",
    "species": "homo_sapiens"
}

Expected Steps

1. Predict functional effects with VEP
2. Get variant details
3. Get phenotype associations
4. Search PubMed for evidence

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",
    "search-server": "https://scp.intern-ai.org.cn/api/v1/mcp/7/Origene-Search"
}

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():
    
    sessions = {}
    sessions[], _, _ =  connect(, )
    sessions[], _, _ =  connect(, )

    
    
    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())