systems-pharmacology

name: systems_pharmacology description: "Systems Pharmacology Analysis - Systems pharmacology: drug targets, protein interactions, pathway enrichment, and gene expression. Use this skill for systems pharmacology tasks involving get target by name get string network interaction get functional enrichment get gene expression across cancers. Combines 4 tools from 3 SCP server(s)."

Systems Pharmacology Analysis

Discipline: Systems Pharmacology | Tools Used: 4 | Servers: 3

Description

Systems pharmacology: drug targets, protein interactions, pathway enrichment, and gene expression.

Tools Used

• get_target_by_name from chembl-server (streamable-http) - https://scp.intern-ai.org.cn/api/v1/mcp/4/Origene-ChEMBL
• get_string_network_interaction from string-server (streamable-http) - https://scp.intern-ai.org.cn/api/v1/mcp/6/Origene-STRING
• get_functional_enrichment from string-server (streamable-http) - https://scp.intern-ai.org.cn/api/v1/mcp/6/Origene-STRING
• get_gene_expression_across_cancers from tcga-server (streamable-http) - https://scp.intern-ai.org.cn/api/v1/mcp/11/Origene-TCGA

Workflow

1. Get drug target info
2. Build interaction network
3. Run pathway enrichment
4. Check expression across cancers

Test Case

Input

{
    "target": "EGFR",
    "species": 9606
}

Expected Steps

1. Get drug target info
2. Build interaction network
3. Run pathway enrichment
4. Check expression across cancers

Usage Example

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 = {
    "chembl-server": "https://scp.intern-ai.org.cn/api/v1/mcp/4/Origene-ChEMBL",
    "string-server": "https://scp.intern-ai.org.cn/api/v1/mcp/6/Origene-STRING",
    "tcga-server": "https://scp.intern-ai.org.cn/api/v1/mcp/11/Origene-TCGA"
}

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["chembl-server"], _, _ = await connect("https://scp.intern-ai.org.cn/api/v1/mcp/4/Origene-ChEMBL", "streamable-http")
    sessions["string-server"], _, _ = await connect("https://scp.intern-ai.org.cn/api/v1/mcp/6/Origene-STRING", "streamable-http")
    sessions["tcga-server"], _, _ = await connect("https://scp.intern-ai.org.cn/api/v1/mcp/11/Origene-TCGA", "streamable-http")

    # Execute workflow steps
    # Step 1: Get drug target info
    result_1 = await sessions["chembl-server"].call_tool("get_target_by_name", arguments={})
    data_1 = parse(result_1)
    print(f"Step 1 result: {json.dumps(data_1, indent=2, ensure_ascii=False)[:500]}")

    # Step 2: Build interaction network
    result_2 = await sessions["string-server"].call_tool("get_string_network_interaction", arguments={})
    data_2 = parse(result_2)
    print(f"Step 2 result: {json.dumps(data_2, indent=2, ensure_ascii=False)[:500]}")

    # Step 3: Run pathway enrichment
    result_3 = await sessions["string-server"].call_tool("get_functional_enrichment", arguments={})
    data_3 = parse(result_3)
    print(f"Step 3 result: {json.dumps(data_3, indent=2, ensure_ascii=False)[:500]}")

    # Step 4: Check expression across cancers
    result_4 = await sessions["tcga-server"].call_tool("get_gene_expression_across_cancers", 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())