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ahines99

portco-mcp

by ahines99
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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

    A3.6/5.0

    Scored across 12 tools

    Disambiguation4/5

    Most tools have clearly distinct purposes along the pipeline (start, profile, propose, generate, test, publish). However, list_pending_reviews overlaps with get_run_status (both return pending review items), and submit_mapping_review vs certify_run both handle reviewer decisions with subject_hash, which could cause confusion without close reading.

    Naming Consistency4/5

    Nearly all tools follow a consistent verb_noun snake_case pattern (list_pending_reviews, start_onboarding_run, generate_dbt_artifacts). The lone outlier is healthcheck, which is a noun with no verb, a minor deviation.

    Tool Count5/5

    12 tools is well-scoped for a multi-stage data onboarding pipeline with human review gates, artifact generation, testing, and publishing. Each tool appears to own a distinct lifecycle step, with no redundant entries.

    Completeness4/5

    The core lifecycle is covered: start, status, resume, profile, propose, review, certify, generate, test, publish. Minor gaps exist, such as no cancel/abort run, no list-runs tool, and no way to retrieve generated artifacts or open findings directly for inspection.

    Maintenance

    ActivityMaintained
    ResponsivenessNo issues

    Resources