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mcp-sqlalchemy

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Python
Remote

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    • Data Agent Connector

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    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

    C2.3/5.0

    Scored across 11 tools

    Disambiguation2/5

    Multiple tools have overlapping or unclear purposes, causing confusion. For example, podbc_execute_query and podbc_query_database both execute SQL queries and return results in JSONL format, making them nearly indistinguishable. Additionally, podbc_sparql_func and podbc_virtuoso_support_ai have vague descriptions that don't clearly differentiate their functions from other query tools.

    Naming Consistency4/5

    The naming follows a consistent prefix pattern (podbc_) and uses snake_case throughout, which is predictable. However, there are minor deviations like podbc_spasql_query (likely a typo for SPARQL) and inconsistent verb usage (e.g., get_schemas vs. filter_table_names), but overall the structure is readable and mostly uniform.

    Tool Count4/5

    With 11 tools, the count is reasonable for a database interaction server, covering schema exploration, table queries, and specialized functions. It's slightly on the higher side but still manageable, as each tool appears to serve a distinct technical purpose, though some redundancy exists.

    Completeness3/5

    The toolset covers core database operations like querying, schema retrieval, and table description, but there are notable gaps. For instance, there are no tools for data manipulation (e.g., insert, update, delete) or transaction management, which are essential for a complete SQLAlchemy-like interface. The inclusion of SPARQL and specialized functions adds niche coverage but doesn't fill these basic CRUD gaps.

    Maintenance

    ActivityInactive
    ResponsivenessUnresponsive

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