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schema-guard-mcp

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    • A
      license
      A
      quality
      C
      maintenance
      MCP server that lets AI coding agents (Claude Code, Cursor, Cline) audit Supabase projects for security misconfigurations AND apply the fixes — without leaving the agent. Tools: audit_project, list_findings, preview_fix (BEGIN/ROLLBACK safety), apply_fix (with confirmation), apply_all_fixes (transactional bulk). Closes the audit-fix loop entirely in the agent — other Supabase scanners only report.
      5
      5 npm
      1
      MIT
    • A
      license
      Not graded
      quality
      C
      maintenance
      Enables AI agents to safely query PostgreSQL by intercepting and auditing every generated SQL statement before it reaches the database, blocking destructive commands like DROP/TRUNCATE, unbounded DELETE/UPDATE statements, stacked queries, and SQL injection probes. It exposes tools for validating query safety and enforcing a strict read-only (SELECT/EXPLAIN) policy.
      MIT
    • F
      license
      Not graded
      quality
      D
      maintenance
      Acts as a secure bridge connecting PostgreSQL databases to AI models, enabling natural language querying, schema analysis, and controlled write operations with multi-layer security.
      -
    • A
      license
      Not graded
      quality
      F
      maintenance
      Predeploy security scanner for AI-generated code. 80+ vulnerability patterns across secrets, auth, injection, config, Supabase, and logging. Runs locally, code never leaves your machine. Optional x402 witnessed attestation.
      46 npm
      Apache 2.0
    • A
      license
      Not graded
      quality
      B
      maintenance
      Enables safe, read-only SQL exploration and debugging on Supabase Edge Functions, respecting user JWTs. It inspects schemas, explains query plans, proposes RLS policies, and runs guarded queries without destructive operations.
      MIT
    • A
      license
      Not graded
      quality
      C
      maintenance
      Enforces safety and governance for SQL queries executed by AI agents, providing read-only enforcement, cost estimation, and audit trails.
      Apache 2.0

    TDQS

    A4.2/5.0

    Scored across 3 tools

    Disambiguation5/5

    Each tool has a clearly distinct purpose: comprehensive audit, quick RLS check, and rule listing. No overlap or ambiguity between tool responsibilities.

    Naming Consistency5/5

    All tool names follow a consistent verb_noun pattern with lowercase and underscores (audit_sql, rls_coverage, list_rules). Naming style is uniform and predictable.

    Tool Count5/5

    Three tools is well-scoped for a focused SQL security auditing server. Each tool serves a necessary and non-redundant function without bloat or thinness.

    Completeness5/5

    The domain of static SQL security auditing is fully covered: full audit, quick subset check, and rule enumeration. No obvious missing operations for the server's stated purpose.

    Maintenance

    ActivityStale
    ResponsivenessNo issues