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DimensionHuman MCPBringing Human Capabilities to AI AgentsMartinLoop MCP ServerAn independent control layer that gives AI coding agents budgets, brakes, and receipts
FMRS46 / 100 · D79 / 100 · B
Reliability4 / 2012 / 20
Security and permissions8 / 2018 / 20
Maintenance9 / 2016 / 20
Documentation13 / 2018 / 20
Setup experience12 / 2015 / 20
Best for
  • AI coding agents needing visual debugging capabilities
  • Developers who need automated screenshots and visual analysis
  • Users interested in content generation (images, videos, music, speech)
  • Users who need advanced reasoning capabilities
  • 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
  • Users who only need text-based functionality (overkill)
  • Users seeking a fully local solution without API keys (relies on external AI providers)
  • Users needing audio processing (Ears not yet implemented)
  • 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
  • Requires Google Gemini API key (mandatory)
  • Optional API keys: Minimax, ZhipuAI, ElevenLabs
  • Optional Cloudflare R2 credentials for HTTP transport file uploads
  • Network access to external AI services
  • Local file access to read input files
  • 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
  • API key exposure: keys are stored in config, may be accidentally shared
  • Cost: generative AI usage may incur charges, especially in production
  • Data privacy: files may be uploaded to third-party services (Cloudflare R2) for processing
  • Dependency on external services: relies on availability of Google, Minimax, etc.
  • Configuration errors: invalid API keys or network issues causing failures
  • 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 Desktop, Claude Code, OpenCode, Cline, Cursor, WindsurfClaude Code, Codex, Gemini CLI, Cursor, VS Code, GitHub Copilot, Continue
Tools310