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quelllm-mcp

by MGM-FALCON
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Python
Remote

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    TDQS

    A4.2/5.0

    Scored across 6 tools

    Disambiguation5/5

    Each tool has a clearly distinct purpose: listing models, searching, getting details, comparing, estimating cost, and estimating VRAM. No significant overlap or ambiguity.

    Naming Consistency5/5

    All tool names follow a consistent verb_noun pattern in snake_case (e.g., list_models, estimate_cost), making it easy to predict functionality from the name.

    Tool Count5/5

    With 6 tools, the count is appropriate for the domain of LLM discovery and analysis. Each tool serves a clear purpose without unnecessary bloat or deficiency.

    Completeness4/5

    The toolset covers core operations: listing, searching, detail retrieval, comparison, cost estimation, and VRAM estimation. Minor gaps exist, such as direct pricing for specific models, but the overall workflow is well-supported.

    Maintenance

    ActivitySlowing
    ResponsivenessNo issues

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