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artefact-mcp-server

by artefactventures
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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

    A4.2/5.0

    Scored across 7 tools

    Disambiguation4/5

    Most tools have clearly distinct purposes, but there is some overlap between detect_signals and score_pipeline_health, as both detect signals. However, they are focused on different aspects (signal-only vs. comprehensive health), so ambiguity is low.

    Naming Consistency4/5

    Tool names follow a consistent verb_noun pattern in snake_case, with only minor deviations like 'qualify' (single verb) and 'run_rfm' (verb+acronym). Overall, the pattern is predictable and clear.

    Tool Count5/5

    With 7 tools, the server is well-scoped for its domain of GTM analytics and pipeline management. Each tool provides a distinct function without redundancy, earning its place in the set.

    Completeness4/5

    The tool surface covers core GTM analysis workflows—engine analysis, signal detection, constraint identification, proposal creation, prospect qualification, RFM analysis, and pipeline health. Minor gaps exist, such as no tool for applying changes or performing what-if analysis, but these are not critical for the stated analytical purpose.

    Maintenance

    ActivityNo data
    ResponsivenessUnresponsive

    Resources