---
name: cas-compound-lookup-3bc722ed5f21
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

1. Look up CAS and pricing
2. Get PubChem compound data
3. Get ChEMBL molecule info
4. Analyze chemical structure

## Test Case

### Input
```json
{
    "compound_name": "caffeine"
}
```

### Expected Steps
1. Look up CAS and pricing
2. Get PubChem compound data
3. Get ChEMBL molecule info
4. Analyze chemical structure

## 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](https://scphub.intern-ai.org.cn).

```python
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 = {
    "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, 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["server-30"] = await connect("https://scp.intern-ai.org.cn/api/v1/mcp/30/SciToolAgent-Mat", stack)
        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-28"] = await connect("https://scp.intern-ai.org.cn/api/v1/mcp/28/InternAgent", stack)

        # 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())
```


---
Source attribution: SpectrAI-Initiative
Original project: https://github.com/SpectrAI-Initiative/InnoClaw
License: MIT
License information: https://opensource.org/license/mit
Original upstream instructions; downloaded from Mega AI Hub.

## Upstream license notice

MIT License

Copyright (c) 2026 Gabriel Moreira

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.



# Mega AI Hub resource metadata

Creator / publisher: SpectrAI-Initiative
Original project: https://github.com/SpectrAI-Initiative/InnoClaw
Attribution basis: Upstream repository explicitly recorded in package mirror path

Fields of work: Data & Analytics, Development & Engineering, Education & Research
Roles: Data Scientist, ML / AI Engineer, Researcher
Specialties: API
Tools: Castoprice, Chemicalstructureanalyzer, Chembl Server, Pubchem Server
Country applicability: Country not specified
Classification basis: Source catalog labels
Instruction SHA-256: 28a58c91fca8d16defacf4e2ff00894d02c6b11e30980acc913833784a0e658e
