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interdeep

by mistakeknot
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Python

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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

    B3.4/5.0

    Scored across 4 tools

    Disambiguation5/5

    Each tool has a clearly distinct purpose with no ambiguity: compile_report creates reports from research, extract_batch handles multiple URLs concurrently, extract_content extracts from single URLs with fallback options, and research_status provides system status. The descriptions clearly differentiate their functions, making misselection unlikely.

    Naming Consistency5/5

    All tools follow a consistent verb_noun pattern (compile_report, extract_batch, extract_content, research_status) with clear, descriptive names. There are no deviations in naming conventions, making the set predictable and easy to understand.

    Tool Count4/5

    With 4 tools, the count is reasonable for a research/content extraction server, though slightly lean. Each tool earns its place by covering distinct aspects of the workflow, but the scope might benefit from additional tools for tasks like managing research sources or advanced report formatting.

    Completeness4/5

    The tool surface covers core research and extraction workflows well, including content extraction (single and batch), report compilation, and system status. Minor gaps exist, such as tools for editing reports, managing extracted data, or integrating with external research databases, but agents can work around these with the provided tools.

    Maintenance

    ActivitySlowing
    ResponsivenessNo issues

    Resources