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    • A
      license
      A
      quality
      B
      maintenance
      Enables AI agents to inspect database schemas and run strictly read-only SQL queries with guardrails against destructive statements, multi-statement chaining, and unbounded scans. Supports SQLite natively and PostgreSQL optionally.
      4
      MIT
    • A
      license
      Not graded
      quality
      A
      maintenance
      Enables AI agents to safely explore and query databases across SQLite, PostgreSQL, MySQL, and MSSQL, with schema introspection, natural language queries, and data profiling.
      MIT
    • A
      license
      Not graded
      quality
      B
      maintenance
      Connect AI agents to SQL databases (SQLite, PostgreSQL, MySQL) with a unified interface for querying data, exploring schemas, inserting rows, and exporting results to CSV. Includes safety features like dangerous query blocking and write guards.
      3 npm
      65 PyPI
      MIT
    • A
      license
      A
      quality
      A
      maintenance
      Enables LLMs to safely explore, query, diagnose, and modify relational databases through a unified set of schema introspection, SQL execution, and administration tools. Supports multiple database backends with AST-level read-only guards, automatic LIMIT injection, and explicit opt-in write permissions for DML and DDL.
      6
      476 PyPI
      Apache 2.0
    • A
      license
      A
      quality
      D
      maintenance
      Enables AI agents to safely interact with MySQL/MariaDB databases, supporting read-only queries by default with optional write operations and access control.
      8
      MIT

    TDQS

    A4.7/5.0

    Scored across 11 tools

    Disambiguation5/5

    Each tool targets a distinct step or resource in the database exploration workflow: guide, connections, databases, tables, search_schema, describe, find_ref, sample, count, query, and explain. Descriptions explicitly cross-reference alternatives (e.g., use search_schema when you don't know the table, use query instead of sample for joins), leaving no meaningful overlap.

    Naming Consistency4/5

    All names are lowercase snake_case with no casing or separator inconsistencies. However, the set mixes noun-style list tools (connections, databases, tables) with verb-style action tools (describe, sample, query), so it is not a strict verb_noun pattern throughout.

    Tool Count5/5

    Eleven tools is well within the ideal range and each tool earns its place: discovery, schema inspection, sampling, counting, querying, performance analysis, and reference resolution. No tool feels redundant or excessive for a read-only database assistant.

    Completeness5/5

    The surface covers the full read-only lifecycle from connection discovery through schema browsing, targeted search, structure inspection, sampling, exact counts, general SQL, query plans, and UUID reference resolution. There are no obvious dead ends for the stated purpose, and write operations are intentionally limited by the read-only model.

    Maintenance

    ActivityMaintained
    ResponsivenessNo issues