Analyze protein-protein interaction enrichment using STRING database to identify functional networks and pathway associations.
Scanned 9/7/2026
Install to Claude Code
npx -y skills add InternScience/scp --skill string-ppi-enrichment --agent claude-codeInstalls into .claude/skills of the current project.
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---
name: string-ppi-enrichment
description: Analyze protein-protein interaction enrichment using STRING database to identify functional networks and pathway associations.
license: MIT license
metadata:
skill-author: PJLab
---
# STRING Protein-Protein Interaction Enrichment
## Usage
```python
import asyncio
import json
from mcp.client.streamable_http import streamablehttp_client
from mcp import ClientSession
class OrigeneClient:
def __init__(self, server_url: str, api_key: str):
self.server_url = server_url
self.api_key = api_key
self.session = None
async def connect(self):
try:
self.transport = streamablehttp_client(url=self.server_url, headers={"SCP-HUB-API-KEY": self.api_key})
self.read, self.write, self.get_session_id = await self.transport.__aenter__()
self.session_ctx = ClientSession(self.read, self.write)
self.session = await self.session_ctx.__aenter__()
await self.session.initialize()
return True
except Exception as e:
return False
async def disconnect(self):
if self.session:
await self.session_ctx.__aexit__(None, None, None)
if hasattr(self, 'transport'):
await self.transport.__aexit__(None, None, None)
def parse_result(self, result):
if isinstance(result, dict):
content_list = result.get("content") or []
else:
content_list = getattr(result, "content", []) or []
texts = []
for item in content_list:
if isinstance(item, dict):
if item.get("type") == "text":
texts.append(item.get("text") or "")
else:
if getattr(item, "type", None) == "text":
texts.append(getattr(item, "text", "") or "")
return "".join(texts)
## Initialize and use
client = OrigeneClient("https://scp.intern-ai.org.cn/api/v1/mcp/6/Origene-STRING", "<your-api-key>")
await client.connect()
result = await client.session.call_tool("get_ppi_enrichment", arguments={"identifiers": ["Pax6", "Sox2", "Nanog"], "species": 10090})
print(client.parse_result(result))
await client.disconnect()
```
### Tool: `get_ppi_enrichment`
- Args: `identifiers` (list) - Gene/protein identifiers, `species` (int) - NCBI taxonomy ID
- Returns: Network statistics including edges, clustering coefficient, p-value
### Use Cases
- Protein network analysis, functional module identification, pathway enrichment
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