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Skill v1.0.1
currentAutomated scan100/100internscience/scp/protein-database-crossref
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PublishedJune 17, 2026 at 10:42 AM
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version: "1.0.1" 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
- Get UniProt full entry
- Get NCBI gene data
- Get Ensembl cross-references
- Download PDB structure
Test Case
Input
json
{"uniprot_accession": "P04637","gene": "TP53","pdb_code": "1TUP"}
Expected Steps
- Get UniProt full entry
- Get NCBI gene data
- Get Ensembl cross-references
- Download PDB 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.
python
import asyncioimport jsonfrom mcp import ClientSessionfrom mcp.client.streamable_http import streamablehttp_clientfrom mcp.client.sse import sse_clientSERVERS = {"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, 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, transportdef 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.textreturn str(result)except: return str(result)async def main():# Connect to required serverssessions = {}sessions["uniprot-server"], _, _ = await connect("https://scp.intern-ai.org.cn/api/v1/mcp/10/Origene-UniProt", "streamable-http")sessions["ncbi-server"], _, _ = await connect("https://scp.intern-ai.org.cn/api/v1/mcp/9/Origene-NCBI", "streamable-http")sessions["ensembl-server"], _, _ = await connect("https://scp.intern-ai.org.cn/api/v1/mcp/12/Origene-Ensembl", "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 UniProt full entryresult_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 dataresult_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-referencesresult_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 structureresult_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]}")# Cleanupprint("Workflow complete!")if __name__ == "__main__":asyncio.run(main())