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Works with

Claude CodeClaude DesktopCursorVS CodeClineCodex CLIOpenClaw+ any MCP client

Install to Claude Code

This server doesn't publish a one-line install command. Follow the setup in the source repository.

Summary

Integrity monitor for MCP server ecosystems, providing real-time health checks, drift detection, and cascade impact analysis for any AI agent.

README.md

MCP Health Server

Integrity monitor for MCP server ecosystems. Any AI agent can use these tools to know the real state of its ecosystem in real time.

---

The problem it solves

AI agents fail silently when their tools fail.

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

MCP Health Server gives any agent full visibility into the state of its ecosystem — before things break.

---

Available tools

check_health

Verifies the state of an MCP server in real time. Detects latency, availability, and exposed tools. Compatible with streamable-http and SSE.

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

State of multiple MCP servers in a single call. Runs all checks in parallel.

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

Detects whether a server's behavior has changed compared to its historical baseline.

Finds gradual degradation that traditional uptime alerts never catch.

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

Calculates the cascade impact if a specific service goes down. Shows which other services are affected directly and indirectly.

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"
  }

---

Connect to your agent

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

---

Local setup

# 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

---

Protocol compatibility

Supports both MCP transports with no additional configuration:

  • streamable-http — current standard
  • SSE — Server-Sent Events

---

Skill for AI agents

Includes an optimized SKILL.md for Claude and OpenCode that orchestrates tools automatically based on context.

To activate it in OpenCode, copy SKILL.md to: ~/.config/opencode/skills/mcp-health.md

---

Pricing

| Plan | Price | Limit | |---|---|---| | Free | $0 | 100 checks/day | | Builder | $19/mo | 10,000 checks/day | | Team | $49/mo | Unlimited + email alerts |

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