pubchem_deep_dive
PubChem Deep Dive Analysis - Deep dive into PubChem: compound info, bioassay summary, 3D conformers, synonyms, and general description. Use this skill for chemical databases tasks involving get pubchem compound by cid get assay summary by cid get conformers by cid get compound synonyms by name get general info by compound name. Combines 5 tools from 1 SCP server(s).
Best use case
pubchem_deep_dive is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
PubChem Deep Dive Analysis - Deep dive into PubChem: compound info, bioassay summary, 3D conformers, synonyms, and general description. Use this skill for chemical databases tasks involving get pubchem compound by cid get assay summary by cid get conformers by cid get compound synonyms by name get general info by compound name. Combines 5 tools from 1 SCP server(s).
Teams using pubchem_deep_dive 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
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/pubchem_deep_dive/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How pubchem_deep_dive Compares
| Feature / Agent | pubchem_deep_dive | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
PubChem Deep Dive Analysis - Deep dive into PubChem: compound info, bioassay summary, 3D conformers, synonyms, and general description. Use this skill for chemical databases tasks involving get pubchem compound by cid get assay summary by cid get conformers by cid get compound synonyms by name get general info by compound name. Combines 5 tools from 1 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
# PubChem Deep Dive Analysis
**Discipline**: Chemical Databases | **Tools Used**: 5 | **Servers**: 1
## Description
Deep dive into PubChem: compound info, bioassay summary, 3D conformers, synonyms, and general description.
## Tools Used
- **`get_pubchem_compound_by_cid`** from `pubchem-server` (streamable-http) - `https://scp.intern-ai.org.cn/api/v1/mcp/8/Origene-PubChem`
- **`get_assay_summary_by_cid`** from `pubchem-server` (streamable-http) - `https://scp.intern-ai.org.cn/api/v1/mcp/8/Origene-PubChem`
- **`get_conformers_by_cid`** from `pubchem-server` (streamable-http) - `https://scp.intern-ai.org.cn/api/v1/mcp/8/Origene-PubChem`
- **`get_compound_synonyms_by_name`** from `pubchem-server` (streamable-http) - `https://scp.intern-ai.org.cn/api/v1/mcp/8/Origene-PubChem`
- **`get_general_info_by_compound_name`** from `pubchem-server` (streamable-http) - `https://scp.intern-ai.org.cn/api/v1/mcp/8/Origene-PubChem`
## Workflow
1. Get full compound info
2. Get bioassay summary
3. Get 3D conformers
4. Get all synonyms
5. Get general description
## Test Case
### Input
```json
{
"compound_name": "aspirin",
"cid": 2244
}
```
### Expected Steps
1. Get full compound info
2. Get bioassay summary
3. Get 3D conformers
4. Get all synonyms
5. Get general description
## 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 = {
"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["pubchem-server"] = await connect("https://scp.intern-ai.org.cn/api/v1/mcp/8/Origene-PubChem", stack)
# Execute workflow steps
# Step 1: Get full compound info
result_1 = await sessions["pubchem-server"].call_tool("get_pubchem_compound_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: Get bioassay summary
result_2 = await sessions["pubchem-server"].call_tool("get_assay_summary_by_cid", arguments={})
data_2 = parse(result_2)
print(f"Step 2 result: {json.dumps(data_2, indent=2, ensure_ascii=False)[:500]}")
# Step 3: Get 3D conformers
result_3 = await sessions["pubchem-server"].call_tool("get_conformers_by_cid", arguments={})
data_3 = parse(result_3)
print(f"Step 3 result: {json.dumps(data_3, indent=2, ensure_ascii=False)[:500]}")
# Step 4: Get all synonyms
result_4 = await sessions["pubchem-server"].call_tool("get_compound_synonyms_by_name", arguments={})
data_4 = parse(result_4)
print(f"Step 4 result: {json.dumps(data_4, indent=2, ensure_ascii=False)[:500]}")
# Step 5: Get general description
result_5 = await sessions["pubchem-server"].call_tool("get_general_info_by_compound_name", arguments={})
data_5 = parse(result_5)
print(f"Step 5 result: {json.dumps(data_5, indent=2, ensure_ascii=False)[:500]}")
# Cleanup
print("Workflow complete!")
if __name__ == "__main__":
asyncio.run(main())
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