atc_drug_classification

ATC Drug Classification Lookup - Look up drug in ATC classification: ChEMBL ATC class, FDA drug info, PubChem compound, and mechanism of action. Use this skill for pharmacology tasks involving get atc class by level5 get mechanism of action by drug name get compound by name get drug by name. Combines 4 tools from 3 SCP server(s).

Best use case

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

ATC Drug Classification Lookup - Look up drug in ATC classification: ChEMBL ATC class, FDA drug info, PubChem compound, and mechanism of action. Use this skill for pharmacology tasks involving get atc class by level5 get mechanism of action by drug name get compound by name get drug by name. Combines 4 tools from 3 SCP server(s).

Teams using atc_drug_classification 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/atc_drug_classification/SKILL.md --create-dirs "https://raw.githubusercontent.com/SpectrAI-Initiative/InnoClaw/main/.claude/skills/atc_drug_classification/SKILL.md"

Manual Installation

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

How atc_drug_classification Compares

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

Frequently Asked Questions

What does this skill do?

ATC Drug Classification Lookup - Look up drug in ATC classification: ChEMBL ATC class, FDA drug info, PubChem compound, and mechanism of action. Use this skill for pharmacology tasks involving get atc class by level5 get mechanism of action by drug name get compound by name get drug by name. Combines 4 tools from 3 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

# ATC Drug Classification Lookup

**Discipline**: Pharmacology | **Tools Used**: 4 | **Servers**: 3

## Description

Look up drug in ATC classification: ChEMBL ATC class, FDA drug info, PubChem compound, and mechanism of action.

## Tools Used

- **`get_atc_class_by_level5`** from `chembl-server` (streamable-http) - `https://scp.intern-ai.org.cn/api/v1/mcp/4/Origene-ChEMBL`
- **`get_mechanism_of_action_by_drug_name`** from `fda-drug-server` (streamable-http) - `https://scp.intern-ai.org.cn/api/v1/mcp/14/Origene-FDADrug`
- **`get_compound_by_name`** from `pubchem-server` (streamable-http) - `https://scp.intern-ai.org.cn/api/v1/mcp/8/Origene-PubChem`
- **`get_drug_by_name`** from `chembl-server` (streamable-http) - `https://scp.intern-ai.org.cn/api/v1/mcp/4/Origene-ChEMBL`

## Workflow

1. Get ATC classification
2. Get mechanism of action
3. Get PubChem compound
4. Get ChEMBL drug data

## Test Case

### Input
```json
{
    "atc_code": "C10AA05",
    "drug_name": "atorvastatin"
}
```

### Expected Steps
1. Get ATC classification
2. Get mechanism of action
3. Get PubChem compound
4. Get ChEMBL drug data

## 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 = {
    "chembl-server": "https://scp.intern-ai.org.cn/api/v1/mcp/4/Origene-ChEMBL",
    "fda-drug-server": "https://scp.intern-ai.org.cn/api/v1/mcp/14/Origene-FDADrug",
    "pubchem-server": "https://scp.intern-ai.org.cn/api/v1/mcp/8/Origene-PubChem"
}

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["chembl-server"] = await connect("https://scp.intern-ai.org.cn/api/v1/mcp/4/Origene-ChEMBL", stack)
        sessions["fda-drug-server"] = await connect("https://scp.intern-ai.org.cn/api/v1/mcp/14/Origene-FDADrug", stack)
        sessions["pubchem-server"] = await connect("https://scp.intern-ai.org.cn/api/v1/mcp/8/Origene-PubChem", stack)

        # Execute workflow steps
        # Step 1: Get ATC classification
        result_1 = await sessions["chembl-server"].call_tool("get_atc_class_by_level5", arguments={})
        data_1 = parse(result_1)
        print(f"Step 1 result: {json.dumps(data_1, indent=2, ensure_ascii=False)[:500]}")

        # Step 2: Get mechanism of action
        result_2 = await sessions["fda-drug-server"].call_tool("get_mechanism_of_action_by_drug_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 PubChem compound
        result_3 = await sessions["pubchem-server"].call_tool("get_compound_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: Get ChEMBL drug data
        result_4 = await sessions["chembl-server"].call_tool("get_drug_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())
```

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