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    • A
      license
      Not graded
      quality
      A
      maintenance
      Enables an AI agent to audit an untrusted repository through eight parameterless MCP tools that run ten pinned security scanners inside a hardened container, returning native scanner reports, a run manifest tied to the scanned tree, and an audit log. The agent gets no shell, no target path, and no way to build or execute the audited code, so hostile repositories cannot steer the analysis.
      Apache 2.0
    • A
      license
      B
      quality
      B
      maintenance
      Enables AI agents to run deterministic, fully local static security and compliance audits of code, configurations, and dependencies through 32 MCP tools covering 24 vulnerability categories. It also detects the project stack, generates risk reports and checklists, suggests stack-aware remediations, and re-validates fixes to confirm vulnerabilities were eliminated.
      32
      1
      MIT
    • F
      license
      B
      quality
      C
      maintenance
      Enables AI agents to perform comprehensive, zero-infrastructure codebase analysis through 24 MCP tools, covering security, quality, architecture, type safety, git history, and dead code detection with high precision and local privacy.
      45
      -
    • A
      license
      B
      quality
      C
      maintenance
      Enables AI coding agents to perform evidence-based, read-only audits of supported software projects by exposing bounded project inventory and static-analysis findings for discovery, code review, integration tracing, security, and tests. Reports are returned as Markdown or JSON directly in the tool response, with no code executed or files written.
      8
      281 npm
      MIT
    • A
      license
      Not graded
      quality
      A
      maintenance
      Enables MCP-compatible agents to submit source code for automated SAST/SCA security audits paid via x402 USDC micropayments on Base, returning structured vulnerability findings, CWE IDs, and optional remediated code patches.
      MIT

    TDQS

    A3.7/5.0

    Scored across 2 tools

    Disambiguation4/5

    audit and check are distinct: audit gives a summary across all checks, while check drills into a specific check with filters. The descriptions make the boundary clear, though both deal with findings and could momentarily confuse a new agent.

    Naming Consistency4/5

    Both tools use single, lowercase verbs (audit, check), which is consistent, but they don't follow the common verb_noun pattern. No mixing of conventions, so readability is high.

    Tool Count4/5

    Two tools is slightly under the typical 3-15 range, but they are well-scoped: audit provides the overview and check handles per-check details via a parameterized interface. Each earns its place, though the surface feels minimal.

    Completeness3/5

    Core read functionality is covered: summary and detailed findings with pagination/filtering. However, there is no way to list available check names, manage false positives, or run individual checks directly, which are notable gaps for a code audit workflow.

    Maintenance

    ActivityMaintained
    ResponsivenessNo issues