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aris-mcp

by Knuckles-Team
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Python
Remote

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    TDQS

    B3.4/5.0

    Scored across 9 tools

    Disambiguation4/5

    Most tools target distinct resource+action pairs (list models, list objects, list connections, set attributes), so selection is generally clear. However, aris_get_model (metadata including attributes) overlaps meaningfully with aris_list_model_attributes, and the two ingest tools (ingest_models vs ingest_model_export) require reading descriptions to distinguish bulk ingestion from blob storage.

    Naming Consistency5/5

    All tools use a consistent snake_case aris_ prefix followed by verb_noun patterns (aris_list_models, aris_get_model, aris_set_model_attributes). The convention is predictable throughout, with only minor stylistic variance in the longer ingest names.

    Tool Count5/5

    Nine tools is well-scoped for an ARIS-to-KG bridge: reads, writes, and ingestion paths each have a clear purpose. No tool appears redundant enough to remove, and nothing feels thin.

    Completeness4/5

    The surface covers listing models, inspecting metadata/attributes/objects/connections, writing model and object attributes, and both bulk and blob ingestion. Minor gaps exist: no get_object or object-level create/delete, no model delete, and no tenant/database listing, but core ingestion and writeback workflows are covered.

    Maintenance

    ActivityActive
    ResponsivenessNo issues

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