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MauriceIsrael

SmartMemory

by MauriceIsrael
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Python
Hybrid

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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

    A3.7/5.0

    Scored across 14 tools

    Disambiguation3/5

    Most tools are clearly distinct, but load_custom_rule and suggest_rule both add SPARQL rules with different approval paths, creating ambiguity. Additionally, verify_inference's description mentions accepting/rejecting pending verifications, overlapping with get_pending_verifications and approve_rule.

    Naming Consistency3/5

    All names use snake_case, but retrieval verbs are mixed (list, get, search, query) and rule-related tools use inconsistent actions (load, suggest, approve, reject). The naming is readable but not fully predictable.

    Tool Count5/5

    14 tools is within the ideal 3-15 range and each serves a distinct role in the memory and rule management workflows. The count is well-scoped for the server's purpose.

    Completeness4/5

    Core memory operations (add, remove, query, search) and rule lifecycle (suggest, approve, reject, list) are covered. Minor gaps include no explicit update/merge operation for facts and potential confusion around handling rules extracted by load_document.

    Maintenance

    ActivityInactive
    ResponsivenessNo issues

    Resources