Protein Cross-Database Reference - Cross-reference protein: UniProt entry, NCBI gene, Ensembl xrefs, and PDB structure search. Use this skill for proteomics tasks involving get uniprotkb entry by accession get gene metadata by gene name get xrefs symbol retrieve protein data by pdbcode. Combines 4 tools from 4 SCP server(s).
Scanned 6/6/2026
Install via CLI
openskills install SpectrAI-Initiative/InnoClaw---
name: protein_database_crossref
description: "Protein Cross-Database Reference - Cross-reference protein: UniProt entry, NCBI gene, Ensembl xrefs, and PDB structure search. Use this skill for proteomics tasks involving get uniprotkb entry by accession get gene metadata by gene name get xrefs symbol retrieve protein data by pdbcode. Combines 4 tools from 4 SCP server(s)."
---
# Protein Cross-Database Reference
**Discipline**: Proteomics | **Tools Used**: 4 | **Servers**: 4
## Description
Cross-reference protein: UniProt entry, NCBI gene, Ensembl xrefs, and PDB structure search.
## Tools Used
- **`get_uniprotkb_entry_by_accession`** from `uniprot-server` (streamable-http) - `https://scp.intern-ai.org.cn/api/v1/mcp/10/Origene-UniProt`
- **`get_gene_metadata_by_gene_name`** from `ncbi-server` (streamable-http) - `https://scp.intern-ai.org.cn/api/v1/mcp/9/Origene-NCBI`
- **`get_xrefs_symbol`** from `ensembl-server` (streamable-http) - `https://scp.intern-ai.org.cn/api/v1/mcp/12/Origene-Ensembl`
- **`retrieve_protein_data_by_pdbcode`** from `server-2` (streamable-http) - `https://scp.intern-ai.org.cn/api/v1/mcp/2/DrugSDA-Tool`
## Workflow
1. Get UniProt full entry
2. Get NCBI gene data
3. Get Ensembl cross-references
4. Download PDB structure
## Test Case
### Input
```json
{
"uniprot_accession": "P04637",
"gene": "TP53",
"pdb_code": "1TUP"
}
```
### Expected Steps
1. Get UniProt full entry
2. Get NCBI gene data
3. Get Ensembl cross-references
4. Download PDB 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 = {
"uniprot-server": "https://scp.intern-ai.org.cn/api/v1/mcp/10/Origene-UniProt",
"ncbi-server": "https://scp.intern-ai.org.cn/api/v1/mcp/9/Origene-NCBI",
"ensembl-server": "https://scp.intern-ai.org.cn/api/v1/mcp/12/Origene-Ensembl",
"server-2": "https://scp.intern-ai.org.cn/api/v1/mcp/2/DrugSDA-Tool"
}
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["uniprot-server"] = await connect("https://scp.intern-ai.org.cn/api/v1/mcp/10/Origene-UniProt", stack)
sessions["ncbi-server"] = await connect("https://scp.intern-ai.org.cn/api/v1/mcp/9/Origene-NCBI", stack)
sessions["ensembl-server"] = await connect("https://scp.intern-ai.org.cn/api/v1/mcp/12/Origene-Ensembl", stack)
sessions["server-2"] = await connect("https://scp.intern-ai.org.cn/api/v1/mcp/2/DrugSDA-Tool", stack)
# Execute workflow steps
# Step 1: Get UniProt full entry
result_1 = await sessions["uniprot-server"].call_tool("get_uniprotkb_entry_by_accession", arguments={})
data_1 = parse(result_1)
print(f"Step 1 result: {json.dumps(data_1, indent=2, ensure_ascii=False)[:500]}")
# Step 2: Get NCBI gene data
result_2 = await sessions["ncbi-server"].call_tool("get_gene_metadata_by_gene_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 Ensembl cross-references
result_3 = await sessions["ensembl-server"].call_tool("get_xrefs_symbol", arguments={})
data_3 = parse(result_3)
print(f"Step 3 result: {json.dumps(data_3, indent=2, ensure_ascii=False)[:500]}")
# Step 4: Download PDB structure
result_4 = await sessions["server-2"].call_tool("retrieve_protein_data_by_pdbcode", 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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