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Alternatives to GoSQLX

  • A
    license
    A
    quality
    A
    maintenance
    Allows AI assistants to list tables, read data, and execute SQL queries through a controlled interface, making database exploration and analysis safer and more structured.
    3
    24,187 PyPI
    1,405
    MIT
  • A
    license
    Not graded
    quality
    D
    maintenance
    A Model Context Protocol (MCP) server implementation for DuckDB, providing database interaction capabilities through MCP tools. It would be interesting to have LLM analyze it. DuckDB is suitable for local analysis.
    6,300 PyPI
    179
    MIT
  • A
    license
    B
    quality
    C
    maintenance
    Added support for STDIO mode and SSE mode Added support for multiple SQL execution, separated by ";" Added ability to query database table names and fields based on table comments Added SQL Execution Plan Analysis Added Chinese field to pinyin conversion
    5
    57 PyPI
    250
    MIT

Related Servers

  • A
    license
    Not graded
    quality
    F
    maintenance
    Read-only MCP server for SQL databases (SQL Server, Postgres, SQLite) with multi-server support and three-layer safety using AST validation and linting.
    MIT
  • A
    license
    Not graded
    quality
    C
    maintenance
    Enables MCP-compatible AI agents to run policy-checked SQL against MySQL through a self-hosted Streamable HTTP endpoint, where each request is authenticated by bearer token and constrained by role-based statement allowlists, timeouts, and row limits. It also provides identity introspection, admin-gated configuration reload, and JSONL audit logging of allowed, denied, and errored queries.
    1
    Apache 2.0
  • A
    license
    Not graded
    quality
    B
    maintenance
    Enables static, database-free SQL health checks that return rule-based findings and verdicts, propose executable fixes, and verify rewrites are equivalent while comparing execution plans and suggesting indexes. Supports batch/file/git-diff review for CI gating, all at zero-dependency Tier0.
    MIT
  • F
    license
    Not graded
    quality
    D
    maintenance
    Provides SQL parsing, transpilation, formatting, extraction, and condition injection via MCP protocol, enabling agents to validate, analyze, and transform SQL.
    -
  • A
    license
    Not graded
    quality
    C
    maintenance
    Enables MCP clients to explore and query Postgres, MySQL, and BigQuery databases—listing schemas and tables, describing columns, sampling rows, running read-only SQL, and, when permitted, executing writes—with schema allowlists, hidden columns, response budgets, and audit logging. Runs on Node/Docker over stdio or Streamable HTTP, or as a Cloudflare Worker with OAuth and Hyperdrive.
    101 npm
    MIT
  • A
    license
    Not graded
    quality
    A
    maintenance
    Deterministic SQL static analysis and query-equivalence checking for Postgres, MySQL, SQLite, and SQL Server. Tokenizes locally before forwarding to the API.
    8
    Apache 2.0

TDQS

A4.1/5.0

Scored across 7 tools

Disambiguation4/5

Each tool has a distinct primary action: format, parse, validate, lint, security scan, metadata extraction, and a composite analysis report. The main ambiguity is that `analyze_sql` overlaps with all the individual tools by running them concurrently, so an agent may sometimes choose the composite instead of a targeted tool. Descriptions mitigate this by framing `analyze_sql` as a full review, but the boundary is not perfectly sharp.

Naming Consistency4/5

Six of seven tools follow a clear verb_noun snake_case pattern: format_sql, parse_sql, analyze_sql, extract_metadata, lint_sql, and validate_sql. `security_scan` deviates slightly because it is a noun compound rather than verb_noun, but it remains readable and thematically consistent.

Tool Count5/5

Seven tools is well-scoped for a SQL analysis and formatting server. Each tool corresponds to a meaningful operation, and there are no redundant or trivial entries beyond the intentional composite `analyze_sql`.

Completeness5/5

The surface covers the full SQL analysis lifecycle: validation, parsing, formatting, linting, security scanning, metadata extraction, and a composite review. There are no obvious dead ends for the stated domain.

Maintenance

ActivityMaintained
ResponsivenessResponsive