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pipelines-mcp

by maxim-at-reveliolabs
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Python
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    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

    A3.8/5.0

    Scored across 8 tools

    Disambiguation5/5

    Each tool has a clearly distinct resource/action pairing: jobs, pods, job configs, pod configs, and two log types. Pipeline worker logs and service logs are the only overlapping pair, but the names and descriptions cleanly separate them.

    Naming Consistency5/5

    All tools follow a consistent verb_noun pattern using get_ or list_ prefixes. The resource nouns are uniform and predictable, with job/config/pod/log/service modifiers making the hierarchy easy to infer.

    Tool Count5/5

    Eight tools is a well-scoped size for a pipeline inspection server. Each tool covers a distinct need without redundancy or surface bloat.

    Completeness4/5

    The set provides solid read-only coverage of jobs, pods, configs, and logs, which matches an observability-focused purose. Minor gaps exist, such as no direct way to list services or aggregate request-level status, but agents can work around these using the existing list and get tools.

    Maintenance

    ActivityMaintained
    ResponsivenessNo issues

    Resources