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AI Model Advisor MCP Server

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    TDQS

    A3.9/5.0

    Scored across 9 tools

    Disambiguation4/5

    Most tools have clearly distinct purposes: listing, getting details, comparing, recommending, estimating cost, etc. However, recommend_model and select_model_for_project overlap in that both provide recommendations; select_model_for_project is explicitly a higher-level aggregation tool, but agents could be uncertain which to use.

    Naming Consistency4/5

    The majority of tools follow a consistent verb_noun snake_case pattern (e.g., list_models, get_model_info, estimate_cost). The exception is whats_new, which deviates from the verb_noun structure but remains clear and fits the domain.

    Tool Count5/5

    With 9 tools, the set is well-scoped for an AI model advisor. Each tool addresses a distinct need, and the count is within the ideal range for a focused server.

    Completeness5/5

    The tool surface covers the full lifecycle of model advisory: discovery (list_models, whats_new), detailed info (get_model_info), recommendation (recommend_model, select_model_for_project), comparison (compare_models), pricing (batch_get_pricing, find_cheapest_provider), and cost estimation (estimate_cost). No significant gaps are apparent.

    Maintenance

    ActivityInactive
    ResponsivenessNo issues

    Resources