Assess wind energy potential and perform site analysis using atmospheric science calculations.
Scanned 9/7/2026
Install to Claude Code
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---
name: wind-site-assessment
description: Assess wind energy potential and perform site analysis using atmospheric science calculations.
license: MIT license
metadata:
skill-author: PJLab
---
# Wind Site Assessment
## Usage
### 1. MCP Server Definition
```python
import asyncio
import json
from mcp.client.streamable_http import streamablehttp_client
from mcp import ClientSession
class AtmSciClient:
"""AtmSci-Tool 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.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:
print(f"✗ connect failure: {e}")
return False
async def disconnect(self):
try:
if self.session:
await self.session_ctx.__aexit__(None, None, None)
if hasattr(self, 'transport'):
await self.transport.__aexit__(None, None, None)
except Exception as e:
print(f"✗ disconnect error: {e}")
def parse_result(self, result):
try:
if hasattr(result, 'content') and result.content:
content = result.content[0]
if hasattr(content, 'text'):
return json.loads(content.text)
return str(result)
except Exception as e:
return {"error": f"parse error: {e}", "raw": str(result)}
```
### 2. Wind Site Assessment Workflow
Evaluate wind energy potential at a specific location.
**Implementation:**
```python
## Initialize client
client = AtmSciClient(
"https://scp.intern-ai.org.cn/api/v1/mcp/35/AtmSci-Tool",
"<your-api-key>"
)
if not await client.connect():
print("connection failed")
exit()
## Input: Wind measurements
wind_speeds = [6.5, 7.2, 8.1, 5.9, 9.3] # m/s at hub height
hub_height = 80 # meters
air_density = 1.225 # kg/m³
## Calculate wind power and assess site viability
# Note: Use appropriate atmospheric science tools
result = await client.session.call_tool(
"wind_power_assessment",
arguments={
"wind_speeds": wind_speeds,
"hub_height": hub_height,
"air_density": air_density
}
)
assessment = client.parse_result(result)
print(f"Average wind speed: {assessment['avg_speed']:.2f} m/s")
print(f"Wind power density: {assessment['power_density']:.2f} W/m²")
print(f"Site classification: {assessment['classification']}")
await client.disconnect()
```
### Use Cases
- Wind farm site selection
- Renewable energy assessment
- Atmospheric boundary layer studies
- Wind resource mapping
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