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String Ppi Enrichment

ASecurity

Analyze protein-protein interaction enrichment using STRING database to identify functional networks and pathway associations.

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  • Added September 11, 2026
datapythonapidatabase

Works with

  • cli
  • api
  • mcp

Security analysis

A100/100

Scanned September 11, 2026

npx -y skills add InternScience/DrClaw --skill string-ppi-enrichment --agent claude-code

Installs into .claude/skills of the current project.

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SKILL.md
---
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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