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Venelin-Videnov

KALEI MCP Server

by Venelin-Videnov
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    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

    ActivitySlowing
    ResponsivenessNo issues

    Resources