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DimensionMCPControlWindows desktop automation server for AI modelsMartinLoop MCP ServerAn independent control layer that gives AI coding agents budgets, brakes, and receipts
FMRS44 / 100 · D79 / 100 · B
Reliability8 / 2012 / 20
Security and permissions6 / 2018 / 20
Maintenance12 / 2016 / 20
Documentation10 / 2018 / 20
Setup experience8 / 2015 / 20
Best for
  • Developers and testers who want to delegate Windows desktop automation to AI in a controlled environment
  • Researchers and AI experimenters needing programmatic desktop control
  • Users building AI agents that require visual feedback
  • 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
  • Non-Windows systems (Windows only)
  • Multi-monitor or non-standard resolutions requiring high click accuracy
  • Production environments with high security requirements without proper safeguards
  • 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
  • Mouse control
  • Keyboard control
  • Window management
  • Screen capture
  • Clipboard access
  • 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
  • This software is experimental and may cause unintended consequences.
  • Direct control of mouse and keyboard can lead to unintended actions or data loss.
  • HTTPS is mandatory for remote deployments to avoid interception.
  • Some operations may require elevated permissions.
  • 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, Codex, Gemini CLI, Cursor, VS Code, GitHub Copilot, Continue
Tools00