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internscience/scp/cas-compound-lookup

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PublishedJune 12, 2026 at 11:31 PM

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version: "1.0.1" name: cas_compound_lookup description: "CAS Number Compound Lookup - Look up compounds by CAS: convert CAS to price/availability, get PubChem data, get ChEMBL info, and structure analysis. Use this skill for chemical information tasks involving CASToPrice get compound by name get molecule by name ChemicalStructureAnalyzer. Combines 4 tools from 4 SCP server(s)."

CAS Number Compound Lookup

Discipline: Chemical Information | Tools Used: 4 | Servers: 4

Description

Look up compounds by CAS: convert CAS to price/availability, get PubChem data, get ChEMBL info, and structure analysis.

Tools Used

`CASToPrice` from server-30 (sse) - https://scp.intern-ai.org.cn/api/v1/mcp/30/SciToolAgent-Mat
`get_compound_by_name` from pubchem-server (streamable-http) - https://scp.intern-ai.org.cn/api/v1/mcp/8/Origene-PubChem
`get_molecule_by_name` from chembl-server (streamable-http) - https://scp.intern-ai.org.cn/api/v1/mcp/4/Origene-ChEMBL
`ChemicalStructureAnalyzer` from server-28 (sse) - https://scp.intern-ai.org.cn/api/v1/mcp/28/InternAgent

Workflow

Look up CAS and pricing
Get PubChem compound data
Get ChEMBL molecule info
Analyze chemical structure

Test Case

Input

json

{
    "compound_name": "caffeine"
}

Expected Steps

Look up CAS and pricing
Get PubChem compound data
Get ChEMBL molecule info
Analyze chemical structure

Usage Example

Note: Replace <YOUR_SCP_HUB_API_KEY> with your own SCP Hub API Key. You can obtain one from the SCP Platform.

python

import asyncio
import json
from mcp import ClientSession
from mcp.client.streamable_http import streamablehttp_client
from mcp.client.sse import sse_client
SERVERS = {
    "server-30": "https://scp.intern-ai.org.cn/api/v1/mcp/30/SciToolAgent-Mat",
    "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-28": "https://scp.intern-ai.org.cn/api/v1/mcp/28/InternAgent"
}
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["server-30"], _, _ = await connect("https://scp.intern-ai.org.cn/api/v1/mcp/30/SciToolAgent-Mat", "sse")
    sessions["pubchem-server"], _, _ = await connect("https://scp.intern-ai.org.cn/api/v1/mcp/8/Origene-PubChem", "streamable-http")
    sessions["chembl-server"], _, _ = await connect("https://scp.intern-ai.org.cn/api/v1/mcp/4/Origene-ChEMBL", "streamable-http")
    sessions["server-28"], _, _ = await connect("https://scp.intern-ai.org.cn/api/v1/mcp/28/InternAgent", "sse")
    # Execute workflow steps
    # Step 1: Look up CAS and pricing
    result_1 = await sessions["server-30"].call_tool("CASToPrice", arguments={})
    data_1 = parse(result_1)
    print(f"Step 1 result: {json.dumps(data_1, indent=2, ensure_ascii=False)[:500]}")
    # Step 2: Get PubChem compound data
    result_2 = await sessions["pubchem-server"].call_tool("get_compound_by_name", arguments={})
    data_2 = parse(result_2)
    print(f"Step 2 result: {json.dumps(data_2, indent=2, ensure_ascii=False)[:500]}")
    # Step 3: Get ChEMBL molecule info
    result_3 = await sessions["chembl-server"].call_tool("get_molecule_by_name", arguments={})
    data_3 = parse(result_3)
    print(f"Step 3 result: {json.dumps(data_3, indent=2, ensure_ascii=False)[:500]}")
    # Step 4: Analyze chemical structure
    result_4 = await sessions["server-28"].call_tool("ChemicalStructureAnalyzer", 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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