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Venelin-Videnov

KALEI MCP Server

by Venelin-Videnov
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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

    B3.4/5.0

    Scored across 13 tools

    Disambiguation3/5

    Most tools are distinct, but kalei_profile_model and kalei_run_start both start profiling runs and return a run ID, while kalei_run_result and kalei_model both return cognitive profile data. The interactive self-run workflow (run_start/run_next/run_act) is clearly explained, but an agent could still misroute calls between the two run modes.

    Naming Consistency3/5

    All tools share the kalei_ prefix, which gives some coherence, but the naming style is mixed: some are verb-oriented (run_start, run_next, run_act, compare), while others are noun-oriented (leaderboard, model, dimensions, providers). The inconsistent verb_noun pattern makes the API less predictable than it could be.

    Tool Count4/5

    At 13 tools, the set is within a reasonable range and each tool supports a coherent profiling/leaderboard domain. The count is slightly heavier than necessary due to two separate run workflows, but no tool feels purely redundant.

    Completeness4/5

    The tool surface covers the core lifecycle: starting runs, monitoring progress, retrieving results, viewing leaderboards, comparing models, and listing dimensions/providers. Minor gaps exist, such as no way to cancel or list past runs, but agents can accomplish the main tasks without dead ends.

    Maintenance

    ActivityInactive
    ResponsivenessNo issues

    Resources