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Ripple-MCP

by 0xYubo
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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

    A4.4/5.0

    Scored across 6 tools

    Disambiguation5/5

    Each tool has a clear, distinct purpose: scan_patterns does regex search across any file, analyze_python_ast does AST-based Python analysis, get_code_context retrieves code snippets, generate_impact_report aggregates results, trace_callers finds callers, and find_definition locates definitions. No two tools overlap ambiguously.

    Naming Consistency5/5

    All tool names follow a consistent verb_noun pattern with lowercase and underscores: scan_patterns, analyze_python_ast, get_code_context, generate_impact_report, trace_callers, find_definition. The naming is uniform and predictable.

    Tool Count5/5

    Six tools is well-scoped for a code impact analysis server. Each tool serves a distinct function in the workflow: searching, analyzing, getting context, tracing callers, finding definitions, and generating reports. No redundancy or unnecessary tools.

    Completeness5/5

    The tool set covers the full lifecycle of impact analysis: search (scan_patterns), precise analysis (analyze_python_ast), context (get_code_context), caller tracing (trace_callers), definition lookup (find_definition), and report generation (generate_impact_report). No obvious gaps for static code change impact assessment.

    Maintenance

    ActivityInactive
    ResponsivenessNo issues

    Resources