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hindocharaj1997

Data Recon MCP Server

by hindocharaj1997
OverviewSchemaSourceRelated ServersDiscussionsAdmin
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

    B3.4/5.0

    Scored across 23 tools

    Disambiguation5/5

    Each tool has a distinct purpose: data source management, discovery, validation, various checks, and job control. No significant overlap; similar tools like compare_table_structures and run_schema_check are differentiated by usage context.

    Naming Consistency5/5

    All tool names follow a consistent verb_noun pattern using lowercase and underscores, e.g., add_datasource, validate_table_exists, run_row_count_check. No naming inconsistencies or mixed conventions.

    Tool Count4/5

    With 23 tools, the set is slightly on the higher side but each tool fulfills a clear role in the reconciliation workflow. The count is justified by the need for separate validation, discovery, and check functions.

    Completeness4/5

    The tool surface covers the core reconciliation lifecycle: source management, discovery, validation, structural and data checks, job creation, monitoring, and results retrieval. Minor gaps like updating datasource configuration exist but do not hinder the primary workflow.

    Maintenance

    ActivityInactive
    ResponsivenessNo issues

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