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biosample_genomics

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BioSample & Genome Cross-Reference - Cross-reference biosample and genome data: NCBI biosample, genome report, sequence reports, and taxonomy. Use this skill for genomics tasks involving get biosample report get genome dataset report by accession get genome sequence reports get taxonomy. Combines 4 tools from 1 SCP server(s).

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BioSample & Genome Cross-Reference

Discipline: Genomics | Tools Used: 4 | Servers: 1

Description

Cross-reference biosample and genome data: NCBI biosample, genome report, sequence reports, and taxonomy.

Tools Used

  • get_biosample_report from ncbi-server (streamable-http) - https://scp.intern-ai.org.cn/api/v1/mcp/9/Origene-NCBI
  • get_genome_dataset_report_by_accession from ncbi-server (streamable-http) - https://scp.intern-ai.org.cn/api/v1/mcp/9/Origene-NCBI
  • get_genome_sequence_reports from ncbi-server (streamable-http) - https://scp.intern-ai.org.cn/api/v1/mcp/9/Origene-NCBI
  • get_taxonomy from ncbi-server (streamable-http) - https://scp.intern-ai.org.cn/api/v1/mcp/9/Origene-NCBI

Workflow

  1. Get biosample report
  2. Get genome dataset report
  3. Get sequence reports
  4. Get taxonomy

Test Case

Input

{
    "biosample": "SAMN15795254",
    "genome_accession": "GCF_000001405.40"
}

Expected Steps

  1. Get biosample report
  2. Get genome dataset report
  3. Get sequence reports
  4. Get taxonomy

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 = {
    "ncbi-server": "https://scp.intern-ai.org.cn/api/v1/mcp/9/Origene-NCBI"
}

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["ncbi-server"], _, _ = await connect("https://scp.intern-ai.org.cn/api/v1/mcp/9/Origene-NCBI", "streamable-http")

    # Execute workflow steps
    # Step 1: Get biosample report
    result_1 = await sessions["ncbi-server"].call_tool("get_biosample_report", arguments={})
    data_1 = parse(result_1)
    print(f"Step 1 result: {json.dumps(data_1, indent=2, ensure_ascii=False)[:500]}")

    # Step 2: Get genome dataset report
    result_2 = await sessions["ncbi-server"].call_tool("get_genome_dataset_report_by_accession", arguments={})
    data_2 = parse(result_2)
    print(f"Step 2 result: {json.dumps(data_2, indent=2, ensure_ascii=False)[:500]}")

    # Step 3: Get sequence reports
    result_3 = await sessions["ncbi-server"].call_tool("get_genome_sequence_reports", arguments={})
    data_3 = parse(result_3)
    print(f"Step 3 result: {json.dumps(data_3, indent=2, ensure_ascii=False)[:500]}")

    # Step 4: Get taxonomy
    result_4 = await sessions["ncbi-server"].call_tool("get_taxonomy", 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())