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mcp-linx

by yamlyoda
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Python
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    Deploy Server
    One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

    TDQS

    C2.5/5.0

    Scored across 59 tools

    Disambiguation3/5

    Most tools target distinct resources (nginx, docker, k8s, pg, redis), but there is notable overlap among health/summary tools: get_diagnostic_context, get_summary, and system_health_check all provide overall status and could be confused. Additionally, nginx_status and nginx_stub_status are similar in name despite different purposes.

    Naming Consistency4/5

    Names are all snake_case and generally follow a logical pattern with domain prefixes (nginx_*, docker_*, k8s_*, linux_*, pg_*, redis_*). However, a few tools like http_check, tls_check, tcp_connect, and get_diagnostic_context deviate from the prefix convention, creating minor inconsistency.

    Tool Count2/5

    59 tools is a very large surface for an MCP server, far exceeding the 25+ threshold that typically feels heavy. While the breadth is understandable for multi-stack diagnostics, many niche tools (e.g., tcpdump_probe, redis_slowlog) could be consolidated or exposed via a more parameterized interface.

    Completeness4/5

    The tool set covers an impressively broad range of diagnostic domains: Nginx, systemd, Docker, network, Prometheus, Loki, Kubernetes, Linux, PostgreSQL, and Redis. It includes health checks, summaries, and detailed metrics, though there are minor gaps like Docker inspect (partially covered by docker_info) and no write/action tools beyond docker_prune.

    Maintenance

    ActivityMaintained
    ResponsivenessNo issues

    Resources