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bioassay_analysis

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Bioassay Data Analysis - Analyze bioassay data: PubChem assay summary, ChEMBL activity search, compound properties, and target info. Use this skill for bioassay science tasks involving get assay summary by cid search activity calculate mol basic info get target by name. Combines 4 tools from 3 SCP server(s).

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Bioassay Data Analysis

Discipline: Bioassay Science | Tools Used: 4 | Servers: 3

Description

Analyze bioassay data: PubChem assay summary, ChEMBL activity search, compound properties, and target info.

Tools Used

  • get_assay_summary_by_cid from pubchem-server (streamable-http) - https://scp.intern-ai.org.cn/api/v1/mcp/8/Origene-PubChem
  • search_activity from chembl-server (streamable-http) - https://scp.intern-ai.org.cn/api/v1/mcp/4/Origene-ChEMBL
  • calculate_mol_basic_info from server-2 (streamable-http) - https://scp.intern-ai.org.cn/api/v1/mcp/2/DrugSDA-Tool
  • get_target_by_name from chembl-server (streamable-http) - https://scp.intern-ai.org.cn/api/v1/mcp/4/Origene-ChEMBL

Workflow

  1. Get PubChem bioassay summary
  2. Search ChEMBL activities
  3. Calculate compound properties
  4. Get target information

Test Case

Input

{
    "cid": 2244,
    "target": "cyclooxygenase"
}

Expected Steps

  1. Get PubChem bioassay summary
  2. Search ChEMBL activities
  3. Calculate compound properties
  4. Get target information

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 = {
    "pubchem-server": "https://scp.intern-ai.org.cn/api/v1/mcp/8/Origene-PubChem",
    "chembl-server": "https://scp.intern-ai.org.cn/api/v1/mcp/4/Origene-ChEMBL",
    "server-2": "https://scp.intern-ai.org.cn/api/v1/mcp/2/DrugSDA-Tool"
}

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["pubchem-server"] = await connect("https://scp.intern-ai.org.cn/api/v1/mcp/8/Origene-PubChem", stack)
        sessions["chembl-server"] = await connect("https://scp.intern-ai.org.cn/api/v1/mcp/4/Origene-ChEMBL", stack)
        sessions["server-2"] = await connect("https://scp.intern-ai.org.cn/api/v1/mcp/2/DrugSDA-Tool", stack)

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

        # Step 2: Search ChEMBL activities
        result_2 = await sessions["chembl-server"].call_tool("search_activity", arguments={})
        data_2 = parse(result_2)
        print(f"Step 2 result: {json.dumps(data_2, indent=2, ensure_ascii=False)[:500]}")

        # Step 3: Calculate compound properties
        result_3 = await sessions["server-2"].call_tool("calculate_mol_basic_info", arguments={})
        data_3 = parse(result_3)
        print(f"Step 3 result: {json.dumps(data_3, indent=2, ensure_ascii=False)[:500]}")

        # Step 4: Get target information
        result_4 = await sessions["chembl-server"].call_tool("get_target_by_name", 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())