cas_compound_lookup

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).

157 stars

Best use case

cas_compound_lookup is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

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).

Teams using cas_compound_lookup should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/cas_compound_lookup/SKILL.md --create-dirs "https://raw.githubusercontent.com/InternScience/DrClaw/main/drclaw/local_skill_hub/science/chemistry/cas_compound_lookup/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/cas_compound_lookup/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How cas_compound_lookup Compares

Feature / Agentcas_compound_lookupStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

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).

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

SKILL.md Source

# 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 `<YOUR_SCP_HUB_API_KEY>` 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 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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