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Related Servers

Alternatives to Open Train MCP

No user-submitted related servers found.

    Related Servers

    • A
      license
      C
      quality
      C
      maintenance
      Enables AI assistants to interact with MLflow experiments, runs, and registered models. Supports browsing experiments, retrieving run details with metrics and parameters, and querying the model registry through natural language.
      7
      MIT
    • A
      license
      B
      quality
      C
      maintenance
      Enables LLM agents to query Weights & Biases experiments, including listing projects, runs, metrics, plotting metrics, and retrieving run details.
      5
      1
      MIT
    • A
      license
      B
      quality
      D
      maintenance
      Enables AI assistants to query and analyze AI agent sessions from observability providers like Shepherd (AIOBS) and Langfuse, allowing users to debug agent runs, compare sessions, track performance, and analyze LLM usage patterns.
      18
      MIT
    • A
      license
      Not graded
      quality
      C
      maintenance
      Enables a local AI agent to investigate service incidents by querying read-only telemetry such as service health, metrics, logs, and traces, then produce verifiable assessments with evidence links and uncertainty.
      Apache 2.0
    • A
      license
      A
      quality
      A
      maintenance
      Connects AI assistants to OpenTelemetry trace backends such as Jaeger, Tempo, Traceloop, and Datadog, enabling natural-language searching of traces and spans, error discovery, and service listing. It also provides LLM-specific analytics, including token usage aggregation, model performance comparison, and identification of the most expensive or slowest traces.
      11
      Apache 2.0

    TDQS

    A3.7/5.0

    Scored across 16 tools

    Disambiguation4/5

    Each tool targets a distinct resource/action, and descriptions clarify boundaries. Minor overlap exists between get_metric_series/get_history and plot_metric/compare_runs, but the set is mostly unambiguous.

    Naming Consistency5/5

    All tools use snake_case with predictable verb_noun patterns: get_*, list_*, download_*, plot_metric, diagnose_run, compare_runs. No inconsistent casing or vague verbs.

    Tool Count4/5

    16 tools is slightly above the typical 3–15 range but reasonable for a rich training-observability domain. Each tool appears to earn its place without obvious redundancy.

    Completeness4/5

    The read-only surface covers runs, metrics, history, logs, files, artifacts, tables, plotting, diagnosis, and comparison well. Minor gaps like full-log download or table discovery exist, but core workflows have no dead ends.

    Maintenance

    ActivityMaintained
    ResponsivenessNo issues