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mcp-town-explorer

by chanys
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Python

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    TDQS

    B3.3/5.0

    Scored across 4 tools

    Disambiguation5/5

    Each tool targets a distinct domain dimension: housing, transportation, education, and public safety. There is no overlap between the four tools, and their purposes are clearly separable by the resource type they query.

    Naming Consistency4/5

    All tools follow a consistent get_[noun] pattern (get_housing, get_distance, get_schools, get_safety). The only minor deviation is that 'distance' refers to a relationship (distance to Boston) while the others refer to town attributes, but the naming is otherwise uniform and predictable.

    Tool Count3/5

    Four tools is a borderline-low count. For a town explorer covering four quality-of-life dimensions (housing, commute, schools, safety), it's coherent but thin—a full explorer might also include taxes, weather, demographics, or amenities.

    Completeness3/5

    The four tools cover major town-comparison dimensions (housing, distance, schools, crime), but several obvious gaps exist: no property-tax data, no median income, no demographics or unemployment figures. An agent comparing towns would likely need more than these four metrics for a thorough assessment.

    Maintenance

    ActivitySlowing
    ResponsivenessNo issues

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