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Drain3 MCP Server

by xinqihuang
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Python
Hybrid

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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

    A3.9/5.0

    Scored across 8 tools

    Disambiguation5/5

    Each tool maps to a distinct operation: training, matching, listing templates, extracting parameters, stats, and persistence. The singular/batch pairs are clearly differentiated by description.

    Naming Consistency5/5

    All tool names follow a consistent verb_noun snake_case pattern, such as train_log, match_log, list_templates, and save_state. Minor length differences do not hurt predictability.

    Tool Count5/5

    Eight tools is well-scoped for a Drain3-focused server. Each tool covers a necessary aspect of the log template mining workflow without redundancy beyond intentional singular/batch variants.

    Completeness4/5

    The core training, matching, template listing, parameter extraction, stats, and persistence workflows are covered. However, there is no explicit load_state or reset/clear operation, which leaves minor gaps in full lifecycle management.

    Maintenance

    ActivitySlowing
    ResponsivenessNo issues

    Resources