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learning-loop-mcp

by tiempor3al
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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

    B3/5.0

    Scored across 11 tools

    Disambiguation3/5

    Most tools have distinct purposes, but several pairs overlap in surface intent: amnesia_check vs amnesia_evaluate both concern continuity/Amnesia validation, and learning_context vs search both return lesson-related content. The descriptions help a careful agent differentiate them, but the boundaries are not immediately obvious.

    Naming Consistency3/5

    All names use snake_case and are readable, but the pattern is mixed: some are verb_noun (capture_outcome, register_solution, reindex_solutions), some are noun phrases (learning_status, learning_context, project_preflight), and some are bare words (index, search, solutions). This is not chaotic, but it lacks a consistent convention.

    Tool Count5/5

    Eleven tools is well within the ideal range for a domain-specific server. Each tool serves a distinct role in the learning-loop lifecycle, and none feel redundant or purely decorative.

    Completeness4/5

    The toolset covers the main learning-loop workflow: preflight, outcome capture, Amnesia validation, indexing, solution registration, status, and retrieval. Minor gaps exist—such as no explicit promotion tool or lesson deletion—but these may be intentional given the append-only and forward-only design.

    Maintenance

    ActivityMaintained
    ResponsivenessNo issues

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