Skip to main content
Glama
LogneBudo

LLMxRay-MCP

by LogneBudo
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Local

Related Servers

Alternatives to LLMxRay-MCP

No user-submitted related servers found.

    Related Servers

    • context-rot-detection

      milos-product-maker
      A
      license
      Not graded
      quality
      F
      maintenance
      Provides AI agents with real-time cognitive health monitoring, detecting context rot through token utilization, retrieval accuracy, and session fatigue analysis.
      22 npm
      13
      MIT

    • Txa_MCP

      TXAVLOG
      A
      license
      C
      quality
      C
      maintenance
      Professional local context management and system diagnostic tools for AI IDEs (Cursor, Trae, Antigravity, Windsurf).
      36
      84 npm
      1
      MIT

    • whats-loaded-mcp

      stcmain
      A
      license
      A
      quality
      A
      maintenance
      Shows what is consuming your agent context window before a session starts: always-loaded skill descriptions ranked by token cost, skills installed more than once under different names, CLAUDE.md/AGENTS.md sizes including what their @import lines pull in, and MCP servers configured across clients. Read-only: no child processes, no network.
      5
      39 npm
      MIT

    • devenv-doctor-mcp

      Madiocre
      A
      license
      Not graded
      quality
      D
      maintenance
      Enables LLM clients to inspect local dev environments—Docker container health, pnpm workspace integrity, and stuck process detection—without manual terminal copy-pasting.
      MIT
    Deploy Server
    Context Every Agent Can ShareAgents share what they learn, hand off work, and keep it when you switch models. Start with 5 GB free.fulcradynamics.comAd

    TDQS

    A3.9/5.0

    Scored across 3 tools

    Disambiguation4/5

    Each tool targets a distinct aspect: diagnosing problems, measuring the latest turn, and listing available models. The two turn-related tools could be momentarily confused for performance questions, but their descriptions clearly separate diagnostic findings from raw metrics.

    Naming Consistency4/5

    All names use snake_case consistently, which is a clear pattern. However, diagnose_my_turns is a verb phrase while last_turn_metrics and local_models are noun phrases, so the verb_noun convention is not fully followed.

    Tool Count5/5

    Three tools is a tight, well-scoped set for a diagnostic server; each covers a distinct action (diagnose, measure, list). No bloat and no obvious missing essential tool, so the count fits the purpose.

    Completeness4/5

    The surface covers diagnosing issues, inspecting the latest turn's metrics, and understanding available/local models. Minor gaps exist, such as retrieving metrics for arbitrary past turns or comparing multiple turns, but the core diagnostic lifecycle is present.

    Maintenance

    ActivityMaintained
    ResponsivenessNo issues

    Resources