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suniljavadi

Data Engineering MCP Server

by suniljavadi

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      MIT

    TDQS

    B3.1/5.0

    Scored across 9 tools

    Disambiguation4/5

    Most tools target distinct resources and actions: job status, logs, history, schema, SQL validation/execution, documentation, incidents, and failure analysis are clearly separated. The only mild overlap is get_job_status versus get_job_history, since both relate to recent execution state, but the descriptions clarify that one returns the latest status and the other returns a list of executions.

    Naming Consistency5/5

    All tool names follow a consistent verb_noun pattern using lowercase snake_case, such as get_job_status, validate_sql, search_incidents, and analyze_job_failure. The verb varies based on the action, but the structure is uniform and predictable.

    Tool Count5/5

    Nine tools is well-scoped for a data engineering support server. Each tool serves a clear purpose across job inspection, read-only database access, documentation and incident lookup, and failure analysis without unnecessary redundancy.

    Completeness4/5

    The tool surface covers the core diagnostic workflow: inspect job execution, analyze schema, validate and run read-only SQL, search runbooks and incidents, and assemble failure evidence. A minor gap is the lack of a way to list all available jobs or tables directly, but search and schema tools help compensate.

    Maintenance

    ActivityMaintained
    ResponsivenessNo issues