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DimensionCodeInspectus MCP ServerLocal-first MCP security scanner for AI-generated appsMartinLoop MCP ServerAn independent control layer that gives AI coding agents budgets, brakes, and receipts
FMRS75 / 100 · B79 / 100 · B
Reliability11 / 2012 / 20
Security and permissions18 / 2018 / 20
Maintenance13 / 2016 / 20
Documentation19 / 2018 / 20
Setup experience14 / 2015 / 20
Best for
  • Security-conscious developers building apps with AI agents like Claude Code, Cursor, or Codex
  • Individuals and small teams who want fully offline, local code scanning with no source upload
  • Teams mapping CWE-keyed findings to code-visible compliance controls
  • Engineering teams scaling AI coding agents while controlling spend
  • Platform teams that need auditable, rollback-aware agent execution records
  • Organizations using multiple agents (Claude, Codex, Gemini) under one governed flow
Not for
  • Teams seeking full compliance certification or runtime security proof (the tool explicitly does neither)
  • Deep audits requiring cross-file/whole-program dataflow or runtime mobile testing
  • Restricted environments that cannot run Node.js ≥22 or install cosign and engine binaries
  • Essential Eight assessments (only ~1 of 8 mitigations is code-evidenced)
  • Developers who just want a simple code-completion helper without run governance
  • Teams unwilling to accept local JSONL run records with HMAC signing
  • Environments without a supported adapter (Claude/Codex/Gemini CLIs, direct provider, or verifier-only)
Required permissions
  • Reads project source and repository files (read-only; never edits or deletes your code)
  • Stores engine data and scan history under ~/.codeinspectus
  • Optionally writes one SBOM file (managed directory by default, or a chosen path)
  • Runs SHA-verified Opengrep/Gitleaks/Trivy binaries as local subprocesses
  • Reads git state for a git-safety recommendation; git operations require user approval and the tool never runs them itself
  • Read/write access to the configured repo root (writable scope restrictable via --allow-path/--deny-path)
  • Ability to invoke the chosen agent CLI (Claude/Codex/Gemini, etc.) and its underlying model account
  • Local disk writes for run records, receipts, and share outputs (share/run-receipt., etc.)
  • Execution of user-configured verifier commands (e.g. npm test)
Risks and side effects
  • Prompt-injection detection is heuristic and immature; findings are worded "potential …" at medium confidence
  • Fixes are applied by your AI agent and need human review; the tool only reports and never edits code
  • Native rule coverage is deliberately narrow (mostly intrafile analysis); do not infer broader coverage than executed packs report
  • Compliance mappings are AI-drafted and maintainer-reviewed with 0 of 96 community-verified — not an audit
  • Engine binaries carry supply-chain risk, mitigated via SHA pinning, though setup/repair still downloads over the network
  • Verifier commands are executed; poorly chosen verifier commands carry security risk despite preflight policy checks
  • Cost and token figures may be estimates (labeled with provenance) and should not be treated as settled accounting
  • Receipt integrity must be verified before use as trustworthy evidence; missing rollback evidence is flagged as EVIDENCE_BOUNDARY
  • Policy defaults come from martin.config.yaml and can be overridden by CLI flags; misconfiguration can loosen safety boundaries
Supported clientsClaude Code, Cursor, VS Code, Codex, Windsurf, Cline, AiderClaude Code, Codex, Gemini CLI, Cursor, VS Code, GitHub Copilot, Continue
Tools60