Skillget

mcp-server

mcp
Guvenlik Denetimi
Uyari
Health Uyari
  • License — License: Apache-2.0
  • Description — Repository has a description
  • Active repo — Last push 0 days ago
  • Low visibility — Only 5 GitHub stars
Code Uyari
  • network request — Outbound network request in src/client.ts
  • process.env — Environment variable access in src/index.ts
Permissions Gecti
  • Permissions — No dangerous permissions requested
Purpose
This server acts as a bridge connecting AI models to the Mackerel monitoring platform. It allows LLMs to retrieve and manage monitoring data such as hosts, metrics, alerts, and dashboards.

Security Assessment
Overall risk: Low. The tool requires a Mackerel API key passed via environment variables to function, which is a secure and standard practice. It makes outbound network requests, but these are strictly necessary to communicate with the Mackerel API endpoints. It does not execute arbitrary shell commands or request dangerous system permissions. No hardcoded secrets were detected in the codebase.

Quality Assessment
The project uses the standard Apache-2.0 license and is actively maintained, with recent updates pushed to the repository. However, it currently has very low community visibility with only 5 GitHub stars. As a result, it has not been extensively peer-reviewed by the broader developer community. It is officially maintained under the Mackerel Labs organization, which adds a layer of organizational trust despite the low star count.

Verdict
Use with caution. While the code itself is secure and does not exhibit dangerous behaviors, the low community adoption means it has not yet been widely battle-tested. Ensure you securely manage your API keys if integrating.
SUMMARY

Local MCP (Model Context Protocol) server for integrating LLMs with Mackerel.

README.md

Mackerel MCP Server

A Model Context Protocol server for interacting with Mackerel.

Configuration

The MCP server can be run either via Docker or npx.

Running via Docker

{
  "mcpServers": {
    "mackerel": {
      "command": "docker",
      "args": [
        "run",
        "--rm",
        "-i",
        "-e",
        "MACKEREL_APIKEY",
        "ghcr.io/mackerelio-labs/mcp-server:latest"
      ],
      "env": {
        "MACKEREL_APIKEY": "${MACKEREL_APIKEY}"
      }
    }
  }
}

Running via npx

{
  "mcpServers": {
    "mackerel": {
      "command": "npx",
      "args": [
        "-y",
        "@mackerel/mcp-server"
      ],
      "env": {
        "MACKEREL_APIKEY": "${MACKEREL_APIKEY}"
      }
    }
  }
}

Available tools

  • list_alerts - Retrieve alerts.
  • get_alert - Retrieve a specific alert.
  • get_alert_logs - Retrieve logs for a specific alert.
  • list_dashboards - Retrieve dashboards.
  • get_dashboard - Retrieve a specific dashboard.
  • update_dashboard - Update a specific dashboard.
  • list_hosts - Retrieve hosts.
  • get_host_metrics - Retrieve metrics data for a specific host.
  • list_services - Retrieve services.
  • get_service_metrics - Retrieve metrics data for a specific service.
  • list_monitors - Retrieve monitor configurations.
  • get_monitor - Retrieve a specific monitor configuration.
  • get_trace - Retrieve trace data by trace ID for distributed tracing analysis.
  • list_traces: - Search and retrieve traces.
  • list_http_server_stats - Retrieve HTTP server statistics.
  • list_db_query_stats - Retrieve database query statistics.

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