KEGG Gene Search
SkillSearchSearch KEGG database for gene information to retrieve pathway associations, functional annotations, and disease links.
Available today. Use it from your connected AI after setup.
No other account needed.
Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the KEGG Gene Search skill
What this skill tells your AI
The instructions your AI receives, as published by spectrai-initiative/innoclaw in .claude/skills/kegg-gene-search/SKILL.md and read by ahel’s review.
Usage
1. MCP Server Definition
import asyncio
import json
from contextlib import AsyncExitStack
from mcp.client.streamable_http import streamablehttp_client
from mcp import ClientSession
class OrigeneClient:
"""Origene-KEGG MCP Client"""
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._stack = AsyncExitStack()
await self._stack.__aenter__()
self.read, self.write, self.get_session_id = await self._stack.enter_async_context(self.transport)
self.session_ctx = ClientSession(self.read, self.write)
self.session = await self._stack.enter_async_context(self.session_ctx)
await self.session.initialize()
return True
except Exception as e:
print(f"✗ connect failure: {e}")
return False
async def disconnect(self):
"""Disconnect from server"""
try:
if hasattr(self, '_stack'):
await self._stack.aclose()
print("✓ already disconnect")
except Exception as e:
print(f"✗ disconnect error: {e}")
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)
2. Gene Search Workflow
Implementation:
## Initialize client
client = OrigeneClient(
"https://scp.intern-ai.org.cn/api/v1/mcp/5/Origene-KEGG",
"<your-api-key>"
)
if not await client.connect():
print("connection failed")
exit()
## Search KEGG genes database
result = await client.session.call_tool(
"kegg_find",
arguments={
"db": "genes",
"query": "p53",
"option": ""
}
)
result_data = client.parse_result(result)
print(result_data)
await client.disconnect()
Tool Descriptions
Origene-KEGG Server:
kegg_find: Search KEGG database- Args:
db(str): Database to search (e.g., "genes", "pathway")query(str): Search queryoption(str): Additional options
- Returns: KEGG gene entries with pathway and functional information
- Args:
Use Cases
- Pathway analysis
- Gene functional annotation
- Disease gene identification
- Systems biology research
Signals
- GitHub stars
- 391
- Forks
- 28
- Last commit
- Aug 2026
Advanced
- Catalog kind
- skill
- Gateway key
kegg-gene-search-spectrai-initiative- Source
- github.com/spectrai-initiative/innoclaw