Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type @ followed by the MCP server name and your instructions, e.g., "@Thermal Sentinel MCP Server check heat risk in Phoenix and Dubai"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Heat-risk monitoring agent powered by the FortyGuard Temperature API. Detects heat waves and temperature anomalies, generates alerts with urban-planning recommendations, and exposes an MCP tool interface. Built for the FortyGuard Hackathon'26 (Agentic AI track).
Live demo: https://thermal-sentinel-agent.vercel.app · GitHub: 0xConsole/thermal-sentinel-agent
Thermal Sentinel is an AI agent that:
Queries the FortyGuard Temperature API for real-time urban temperature data
Detects heat waves and anomalies using Sentinel-style multi-signal anomaly detection (WHO heat bands + z-score + sustained-heat + rate-of-change)
Generates heat-risk alerts with actionable urban-planning recommendations
Exposes 11 tools via the MCP (Model Context Protocol) — any AI agent can call them
Displays a live dashboard with city grid, alerts, charts, and one-click demo
Related MCP server: Weather MCP Server
# Clone
git clone https://github.com/0xConsole/thermal-sentinel-agent.git
cd thermal-sentinel-agent
# Install deps
pip install -r requirements.txt
# Run locally (no API key needed — mock data works out of the box)
uvicorn app.main:app --reload --port 8000
# Open dashboard
open http://localhost:8000export FORTYGUARD_API_KEY="your-api-key"
export FORTYGUARD_API_BASE="https://api.fortyguard.com" # default
uvicorn app.main:app --reload --port 8000┌─────────────────────────────────────────────────────────┐
│ Dashboard UI (static) │
│ REST API + MCP Tool Interface │
├─────────────────────────────────────────────────────────┤
│ FastAPI (app/main.py) │
│ /api/* routes + /mcp/tools /mcp/call │
├─────────────────────────────────────────────────────────┤
│ Agent (app/agent.py) │
│ scan_cities → monitor_city → heat_risk_report │
├──────────────┬───────────────────┬──────────────────────┤
│ FortyGuard │ Anomaly Detector │ Store (SQLite) │
│ Client │ (Sentinel-style) │ /tmp persistence │
│ Real or mock │ 4 signals + score │ readings + alerts │
└──────────────┴───────────────────┴──────────────────────┘Tool | Endpoint | Description |
|
| Scan multiple cities for heat risk |
|
| Current temperature for a city |
|
| Hourly temperature history |
|
| Run anomaly detection |
|
| Deep single-city monitoring |
|
| Consolidated risk report |
|
| Active alerts from log |
|
| Dismiss an alert |
|
| List monitorable cities |
|
| Monitoring statistics |
|
| One-click demo scan |
List tools: GET /mcp/tools
Call tool: POST /mcp/call with {"name": "scan_cities", "arguments": {"cities": ["Dubai", "Phoenix"]}}
Method | Path | Description |
|
| Dashboard UI |
|
| Health check (shows live/mock mode) |
|
| Scan cities |
|
| Current temperature |
|
| Temperature history |
|
| Deep city monitoring |
|
| Heat-risk report |
|
| Active alerts |
|
| Acknowledge alert |
|
| Monitoring stats |
|
| List cities |
|
| One-click demo |
Multi-signal, composite 0-100 risk score:
Signal | Max Points | Catches |
WHO heat-risk band | 40 | Absolute heat level |
Z-score (vs 24h baseline) | 25 | Statistical outlier |
Sustained heat-wave (consecutive ≥38°C) | 20 | Heat wave declaration |
Rate-of-change (≥5°C/hr) | 15 | Rapid shifts |
Severity: info → low → medium → high → critical
thermal-sentinel-agent/
├── api/
│ └── index.py # Vercel entry
├── app/
│ ├── __init__.py
│ ├── main.py # FastAPI app + routes
│ ├── fortyguard_client.py # API client + mock transport
│ ├── anomaly_detector.py # Sentinel-style detection
│ ├── agent.py # Orchestration
│ ├── mcp_server.py # MCP tool registry
│ └── store.py # SQLite persistence
├── static/
│ └── index.html # Dashboard UI
├── CONCEPT.md
├── README.md
├── vercel.json
├── requirements.txt
└── .gitignore✅ Real: FortyGuard API integration (when FORTYGUARD_API_KEY set), anomaly detection engine, MCP tool protocol, alert generation, dashboard UI, Vercel deployment
🔶 Mock (fallback): When no API key, temperature data is generated from per-city climate baselines with realistic diurnal variation and anomaly injection — for zero-credential demos
# Vercel (auto-creates project on first deploy)
vercel --prod --yes --token "$VERCEL_TOKEN"
# Or set env var on Vercel
vercel env add FORTYGUARD_API_KEY productionMIT
FortyGuard Hackathon'26 — Agentic AI track
Prize: $6K + NVIDIA Jetson
Judging: Impact (40%), Technical Execution (35%), Innovation (15%), Communication (10%)
See CONCEPT.md for full concept and judging-criteria alignment
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