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DimensionMCP DefenderAutomatically protects MCP traffic in AI appsMartinLoop MCP ServerAn independent control layer that gives AI coding agents budgets, brakes, and receipts
FMRS36 / 100 · D79 / 100 · B
Reliability5 / 2012 / 20
Security and permissions9 / 2018 / 20
Maintenance7 / 2016 / 20
Documentation7 / 2018 / 20
Setup experience8 / 2015 / 20
Best for
  • Developers using Cursor, Claude, Visual Studio Code or Windsurf who want to protect their MCP traffic
  • Users who want signature-based alerting and blocking at the MCP tool call level
  • 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 are not on Mac or do not use the supported AI clients listed above
  • Users expecting to install an MCP server via a client config file rather than a desktop app
  • Scenarios requiring a server-side or cloud-centralized MCP security gateway (not described in the source)
  • 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
  • Proxying MCP tool call requests and responses between AI apps and MCP servers in order to intercept them
  • Inspecting intercepted request and response content locally to match signatures
  • 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
  • The source does not describe the signature set or detection coverage, so misses are possible
  • All MCP traffic is proxied through the desktop app, so proxy issues could affect normal tool calls in AI apps
  • Allow-or-block decisions on suspected harmful content depend on the user, and false positives may block legitimate calls
  • The source does not describe how data is processed or stored, so privacy impact should be assessed independently
  • 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