Agent calls tool → tool responds slowly or incorrectly → agent makes wrong decision
                                                        → nobody knows why

check_health("https://my-server.com/mcp")

→ {
    "status": "healthy",
    "latency_ms": 226,
    "tools_available": ["ping", "get_time", "get_random_metric"],
    "uptime_24h": 99.5
  }

get_summary([
  "https://server-a.com/mcp",
  "https://server-b.com/mcp"
])

→ {
    "total": 2,
    "healthy": 1,
    "degraded": 1,
    "unhealthy": 0,
    "ecosystem_health_score": 50.0
  }

check_drift("https://my-server.com/mcp", baseline_days=7)

→ {
    "drift_detected": false,
    "baseline_avg_latency_ms": 93.7,
    "current_latency_ms": 93.9,
    "overall_severity": "NONE"
  }

calculate_blast_radius(
  "auth-mcp",
  ["data-mcp", "trading-mcp", "report-mcp"]
)

→ {
    "directly_affected": ["data-mcp", "trading-mcp"],
    "cascade_affected": ["report-mcp"],
    "ecosystem_impact_percent": 100.0,
    "severity": "CRITICAL"
  }

{
  "mcpServers": {
    "mcp-health": {
      "url": "https://mcp-health-server.onrender.com/mcp"
    }
  }
}

# 1. Clone the repository
git clone https://github.com/caio313/mcp-health-server
cd mcp-health-server

# 2. Create virtual environment and install dependencies
python -m venv venv
source venv/bin/activate
pip install -r requirements.txt

# 3. Configure environment variables
cp .env.example .env
# Edit .env with your DATABASE_URL

# 4. Initialize the database
python -c "import asyncio; from core.db import init_db; asyncio.run(init_db())"

# 5. Run the server
python main.py
# Available at: http://localhost:8000/mcp