wems-mcp-server
A powerful MCP server that connects AI assistants to authoritative natural hazard data sources, enabling monitoring of earthquakes, tsunamis, volcanoes, and solar events with configurable alerts and webhooks.
README
🌍 WEMS - World Event Monitoring System
<!-- mcp-name: io.github.heliosarchitect/wems -->
🚨 Real-time Natural Hazard Monitoring for AI Agents
A powerful Model Context Protocol (MCP) server that connects AI assistants to authoritative natural hazard data sources. Monitor earthquakes, tsunamis, volcanoes, and solar events with configurable alerts and webhooks.
🤖 AI Agents: Skip scanning this repo. Read
AI.TOCfirst — it's a 500-token project map. Then useAI.INDEXto find specific functions andAI.REGISTERfor env vars, APIs, and config. This project uses the LBF AI Navigation Standard.
⚡ Key Features
- 🌋 9+ Authoritative Data Sources: USGS, NOAA, Smithsonian GVP, NHC, NIFC, OpenAQ, DHS, State Dept, CISA, US Drought Monitor
- 🎯 Real-time Monitoring: Live data feeds with customizable thresholds
- 🔔 Smart Alerts: Webhook notifications for critical events
- 🗺️ Geographic Filtering: Target specific regions or global coverage
- 🔧 Zero Configuration: Works out-of-the-box, configure only what you need
- 🐳 Production Ready: Docker support, comprehensive error handling
Natural Hazards Covered
| Hazard Type | Data Source | Coverage |
|---|---|---|
| 🌊 Earthquakes | USGS | Global, magnitude filtering |
| 🌊 Tsunamis | NOAA PTWC + CTWC | Global ocean basins |
| 🌋 Volcanoes | Smithsonian GVP + USGS | Global volcanic activity |
| ☀️ Solar Events | NOAA SWPC | Solar flares, CMEs, geomagnetic storms |
| 🌞 Space Weather Alerts | NOAA SWPC | Active space weather alerts & warnings |
| 🌀 Hurricanes | NHC + NWS | Atlantic & Pacific tropical cyclones |
| 🔥 Wildfires | NWS + NIFC | Fire weather alerts & active perimeters |
| ⛈️ Severe Weather | NWS Alerts | Tornadoes, thunderstorms, floods, winter storms |
| 💨 Air Quality | OpenAQ | Global AQI, PM2.5, PM10, O₃, NO₂, SO₂, CO |
| 🌵 Drought Conditions | US Drought Monitor | US state drought levels (D0-D4) + trends |
| 🛡️ Threat Advisories | DHS NTAS + State Dept + CISA | Terrorism, travel risk, cyber threats |
🚀 Quick Start
Install via PyPI (Recommended)
pip install wems-mcp-server
Or install from source
git clone https://github.com/heliosarchitect/wems-mcp-server.git
cd wems-mcp-server
pip install -r requirements.txt
Basic Usage
# Run as MCP server (connects to AI assistants)
python -m wems_mcp_server
# Test earthquake monitoring
python -c "
import asyncio
from wems_mcp_server import check_earthquakes
print(asyncio.run(check_earthquakes(min_magnitude=6.0)))
"
One-command AI Alerting Setup (Relay + n8n)
bash scripts/setup_wems_alerting_ai.sh
This will:
- install/start
wems-unified-relay.service - upsert and activate the unified n8n ingest workflow
- wire tracker posting credentials automatically
Example Output
{
"earthquakes_found": 3,
"events": [
{
"magnitude": 7.2,
"location": "67 km SW of Tres Picos, Mexico",
"time": "2024-02-13T14:30:15Z",
"depth": 35.8,
"tsunami_threat": true
}
]
}
MCP Tools
| Tool | Description |
|---|---|
check_earthquakes |
Query recent earthquake activity |
check_solar |
Monitor space weather (K-index, flares, CMEs) |
check_volcanoes |
Track volcanic activity alerts |
check_tsunamis |
Monitor tsunami warnings |
check_hurricanes |
Track tropical cyclones & forecast tracks |
check_wildfires |
Fire weather alerts & active perimeters |
check_severe_weather |
Monitor tornadoes, thunderstorms, flash floods |
check_floods |
Flood warnings & USGS river gauge data |
check_air_quality |
AQI monitoring with pollutant data |
check_threat_advisories |
Terrorism, travel risk & cyber threat monitoring |
check_space_weather_alerts |
Active space weather alerts & warnings from NOAA SWPC |
check_drought_status |
US state drought conditions with D0-D4 levels (Premium) |
configure_alerts |
Update alert thresholds and webhooks |
fuse_multi_source_incidents |
Multi-source incident fusion (feature-flagged) |
Configuration
alerts:
earthquake:
min_magnitude: 6.0
regions: ["US", "Caribbean", "Pacific"]
webhook: "https://your-endpoint.com/earthquake"
solar:
min_kp_index: 7 # Geomagnetic storm threshold
webhook: "https://your-endpoint.com/solar"
volcano:
alert_levels: ["WARNING", "WATCH"]
webhook: "https://your-endpoint.com/volcano"
tsunami:
enabled: true
regions: ["pacific", "atlantic", "indian"]
webhook: "https://your-endpoint.com/tsunami"
Data Sources
- USGS Earthquake Hazards Program
- NOAA Pacific Tsunami Warning Center
- NOAA Central Tsunami Warning Center
- Smithsonian Global Volcanism Program
- NOAA Space Weather Prediction Center
- National Hurricane Center (NHC)
- National Interagency Fire Center (NIFC)
- NWS Alerts API
- OpenAQ (Global Air Quality)
- DHS National Terrorism Advisory System (NTAS)
- U.S. State Department Travel Advisories
- CISA Cybersecurity Advisories
OpenClaw Integration
Add to your OpenClaw configuration:
{
"mcpServers": {
"wems": {
"command": "python3",
"args": ["/path/to/wems-mcp-server/wems_mcp_server.py"],
"env": {
"WEMS_CONFIG": "/path/to/config.yaml"
}
}
}
}
🎯 Use Cases
- 🏢 Enterprise Risk Management: Automated threat assessment for global operations
- 📺 News Organizations: Real-time natural disaster reporting and alerts
- 🔬 Research Institutions: Data collection for scientific analysis
- 🏠 Personal Safety: Location-specific hazard monitoring for families
- 🤖 AI Emergency Response: Integration with disaster response chatbots
- 📱 Alert Systems: Custom notification workflows for critical events
🔧 Advanced Configuration
# config.yaml - Full customization example
alerts:
earthquake:
min_magnitude: 6.0
regions: ["US", "Caribbean", "Pacific"]
webhook: "https://your-endpoint.com/earthquake"
solar:
min_kp_index: 7 # G3+ geomagnetic storm
webhook: "https://your-endpoint.com/solar"
volcano:
alert_levels: ["WARNING", "WATCH"]
regions: ["Cascade Range", "Ring of Fire"]
webhook: "https://your-endpoint.com/volcano"
tsunami:
enabled: true
regions: ["pacific", "atlantic", "indian"]
webhook: "https://your-endpoint.com/tsunami"
📊 Monitoring Dashboard
Pair with monitoring tools for comprehensive coverage:
# Example: Send earthquake data to monitoring system
curl -X POST https://your-monitoring.com/api/events \
-H "Content-Type: application/json" \
-d "$(python -c 'import wems; print(wems.get_recent_earthquakes())')"
💳 Billing & Monetization (Current)
WEMS now includes Stripe metering scaffolding and affordable default pricing.
Current pricing defaults
- Free tier: 5,000 calls per rolling 30 days
- 0–100,000 calls: $0.0010/call
- 100,001–500,000 calls: $0.0008/call
- 500,001+ calls: $0.0006/call
Accessory call weights (default)
- Most tools:
1unit check_space_weather_alerts:2unitsfuse_multi_source_incidents:3units
Billing config
See: config/wems_stripe_billing.json
Key fields:
event_nameapi_key_to_customerbilling_units.defaultbilling_units.by_toolpricing.free_calls_per_rolling_30dpricing.tiers[]
Stripe key source
STRIPE_API_KEYorSTRIPE_SECRET_KEY(direct env)
WEMS uses best-effort lookup and never blocks alerting if billing key resolution fails.
Built with ❤️ for the AI community by Helios 🌞
Part of the expanding OpenClaw ecosystem
推荐服务器
Baidu Map
百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。
Playwright MCP Server
一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。
Magic Component Platform (MCP)
一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。
Audiense Insights MCP Server
通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。
VeyraX
一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。
graphlit-mcp-server
模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。
Kagi MCP Server
一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。
e2b-mcp-server
使用 MCP 通过 e2b 运行代码。
Neon MCP Server
用于与 Neon 管理 API 和数据库交互的 MCP 服务器
Exa MCP Server
模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。