// Antibody-Target Analysis - Analyze an antibody target: UniProt protein info, InterPro domains, protein properties, and biotherapeutic data from ChEMBL. Use this skill for immunology tasks involving get uniprotkb entry by accession query interpro ComputeProtPara get biotherapeutic by name. Combines 4 tools from 4 SCP server(s).
Multi-Omics Integration - Integrate transcriptomics (TCGA), proteomics (UniProt), pathway enrichment (STRING), and metabolic pathway (KEGG) data for a target gene. Outputs a unified JSON report combining expression profiles, protein annotations, enriched pathways, and KEGG pathway details.
ADMET & Drug-Likeness Report - Generate comprehensive ADMET and drug-likeness report: molecular properties, H-bond analysis, hydrophobicity, topology, and ADMET prediction. Use this skill for medicinal chemistry tasks involving calculate mol basic info calculate mol hbond calculate mol hydrophobicity calculate mol topology pred molecule admet. Combines 5 tools from 2 SCP server(s).
Affinity Maturation Pipeline - Affinity maturation: compute binding affinity, predict mutations, compute hydrophilicity, and predict drug-target interaction. Use this skill for antibody engineering tasks involving ComputeAffinityCalculator zero shot sequence prediction ComputeHydrophilicity PredictDrugTargetInteraction. Combines 4 tools from 3 SCP server(s).
Alanine Scanning Mutagenesis Pipeline - Alanine scanning: design scan, compute properties for each mutant, predict interactions, and compare. Use this skill for protein biochemistry tasks involving AlanineScanningDesigner ComputeProtPara PredictDrugTargetInteraction calculate protein sequence properties. Combines 4 tools from 3 SCP server(s).
Ring System Analysis - Analyze ring systems: count aliphatic carbocycles, analyze aromaticity, compute topology, and structure complexity. Use this skill for organic chemistry tasks involving GetAliphaticCarbocyclesNum AromaticityAnalyzer calculate mol topology calculate mol structure complexity. Combines 4 tools from 3 SCP server(s).
AlphaFold Structure Analysis Pipeline - AlphaFold pipeline: download predicted structure, predict pockets, extract sequence, and compute properties. Use this skill for computational biology tasks involving download alphafold structure run fpocket extract pdb sequence calculate pdb basic info. Combines 4 tools from 3 SCP server(s).
| name | antibody_target_analysis |
| description | Antibody-Target Analysis - Analyze an antibody target: UniProt protein info, InterPro domains, protein properties, and biotherapeutic data from ChEMBL. Use this skill for immunology tasks involving get uniprotkb entry by accession query interpro ComputeProtPara get biotherapeutic by name. Combines 4 tools from 4 SCP server(s). |
Discipline: Immunology | Tools Used: 4 | Servers: 4
Analyze an antibody target: UniProt protein info, InterPro domains, protein properties, and biotherapeutic data from ChEMBL.
get_uniprotkb_entry_by_accession from uniprot-server (streamable-http) - https://scp.intern-ai.org.cn/api/v1/mcp/10/Origene-UniProtquery_interpro from server-1 (sse) - https://scp.intern-ai.org.cn/api/v1/mcp/1/VenusFactoryComputeProtPara from server-29 (sse) - https://scp.intern-ai.org.cn/api/v1/mcp/29/SciToolAgent-Bioget_biotherapeutic_by_name from chembl-server (streamable-http) - https://scp.intern-ai.org.cn/api/v1/mcp/4/Origene-ChEMBL{
"uniprot_accession": "P04637",
"protein_sequence": "MEEPQSDPSVEPPLSQETFS"
}
Note: Replace
<YOUR_SCP_HUB_API_KEY>with your own SCP Hub API Key. You can obtain one from the SCP Platform.
import asyncio
import json
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",
"server-1": "https://scp.intern-ai.org.cn/api/v1/mcp/1/VenusFactory",
"server-29": "https://scp.intern-ai.org.cn/api/v1/mcp/29/SciToolAgent-Bio",
"chembl-server": "https://scp.intern-ai.org.cn/api/v1/mcp/4/Origene-ChEMBL"
}
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["uniprot-server"], _, _ = await connect("https://scp.intern-ai.org.cn/api/v1/mcp/10/Origene-UniProt", "streamable-http")
sessions["server-1"], _, _ = await connect("https://scp.intern-ai.org.cn/api/v1/mcp/1/VenusFactory", "sse")
sessions["server-29"], _, _ = await connect("https://scp.intern-ai.org.cn/api/v1/mcp/29/SciToolAgent-Bio", "sse")
sessions["chembl-server"], _, _ = await connect("https://scp.intern-ai.org.cn/api/v1/mcp/4/Origene-ChEMBL", "streamable-http")
# Execute workflow steps
# Step 1: Get full UniProt 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 domain annotations
result_2 = await sessions["server-1"].call_tool("query_interpro", arguments={})
data_2 = parse(result_2)
print(f"Step 2 result: {json.dumps(data_2, indent=2, ensure_ascii=False)[:500]}")
# Step 3: Compute protein parameters
result_3 = await sessions["server-29"].call_tool("ComputeProtPara", arguments={})
data_3 = parse(result_3)
print(f"Step 3 result: {json.dumps(data_3, indent=2, ensure_ascii=False)[:500]}")
# Step 4: Search ChEMBL biotherapeutics
result_4 = await sessions["chembl-server"].call_tool("get_biotherapeutic_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())