'Bioassay Data Analysis - Analyze bioassay data: PubChem assay summary,
Scanned 9/11/2026
Install to Claude Code
npx -y skills add InternScience/DrClaw --skill bioassay_analysis --agent claude-codeInstalls into .claude/skills of the current project.
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---
name: bioassay_analysis
description: 'Bioassay Data Analysis - Analyze bioassay data: PubChem assay summary,
ChEMBL activity search, compound properties, and target info. Use this skill for
bioassay science tasks involving get assay summary by cid search activity calculate
mol basic info get target by name. Combines 4 tools from 3 SCP server(s).'
i18n:
zh:
description: 生物测定数据分析。
---
# Bioassay Data Analysis
**Discipline**: Bioassay Science | **Tools Used**: 4 | **Servers**: 3
## Description
Analyze bioassay data: PubChem assay summary, ChEMBL activity search, compound properties, and target info.
## Tools Used
- **`get_assay_summary_by_cid`** from `pubchem-server` (streamable-http) - `https://scp.intern-ai.org.cn/api/v1/mcp/8/Origene-PubChem`
- **`search_activity`** from `chembl-server` (streamable-http) - `https://scp.intern-ai.org.cn/api/v1/mcp/4/Origene-ChEMBL`
- **`calculate_mol_basic_info`** from `server-2` (streamable-http) - `https://scp.intern-ai.org.cn/api/v1/mcp/2/DrugSDA-Tool`
- **`get_target_by_name`** from `chembl-server` (streamable-http) - `https://scp.intern-ai.org.cn/api/v1/mcp/4/Origene-ChEMBL`
## Workflow
1. Get PubChem bioassay summary
2. Search ChEMBL activities
3. Calculate compound properties
4. Get target information
## Test Case
### Input
```json
{
"cid": 2244,
"target": "cyclooxygenase"
}
```
### Expected Steps
1. Get PubChem bioassay summary
2. Search ChEMBL activities
3. Calculate compound properties
4. Get target information
## 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 = {
"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-2": "https://scp.intern-ai.org.cn/api/v1/mcp/2/DrugSDA-Tool"
}
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["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-2"], _, _ = await connect("https://scp.intern-ai.org.cn/api/v1/mcp/2/DrugSDA-Tool", "streamable-http")
# Execute workflow steps
# Step 1: Get PubChem bioassay summary
result_1 = await sessions["pubchem-server"].call_tool("get_assay_summary_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: Search ChEMBL activities
result_2 = await sessions["chembl-server"].call_tool("search_activity", arguments={})
data_2 = parse(result_2)
print(f"Step 2 result: {json.dumps(data_2, indent=2, ensure_ascii=False)[:500]}")
# Step 3: Calculate compound properties
result_3 = await sessions["server-2"].call_tool("calculate_mol_basic_info", arguments={})
data_3 = parse(result_3)
print(f"Step 3 result: {json.dumps(data_3, indent=2, ensure_ascii=False)[:500]}")
# Step 4: Get target information
result_4 = await sessions["chembl-server"].call_tool("get_target_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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