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Compare scores, permissions, risks, and fit in one decision-focused table.

DimensionInfrawise MCP ServerGive your AI coding assistant deterministic awareness of your AWS and database infrastructureMartinLoop MCP ServerAn independent control layer that gives AI coding agents budgets, brakes, and receipts
FMRS64 / 100 · C79 / 100 · B
Reliability8 / 2012 / 20
Security and permissions12 / 2018 / 20
Maintenance14 / 2016 / 20
Documentation17 / 2018 / 20
Setup experience13 / 2015 / 20
Best for
  • Teams building on AWS with TypeScript/JavaScript/Python
  • Developers who want AI assistants to ground code generation in real infrastructure
  • Engineering teams wanting infrastructure anti-pattern gates in CI
  • 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
  • Projects not using AWS or the supported databases/messaging services
  • Tooling that must provision or modify infrastructure (Infrawise is read-only)
  • Code-level correlation in languages other than TypeScript/JS/Python (infrastructure-level analysis still works)
  • 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
  • AWS credentials via your existing credential chain (minimum dynamodb:ListTables/DescribeTable; full read-only IAM policy in docs)
  • Optional read-only PostgreSQL/MySQL/MongoDB connections (read-only user recommended)
  • SSO profiles require aws sso login first
  • 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
  • Reads infrastructure metadata via AWS APIs and DB connections; read-only and local, but use least-privilege credentials
  • Python code scanning requires python3 on PATH
  • Some supply-chain scanners may flag the 'infra' prefix as deceptive naming (author states this is a false positive; project is independent and unaffiliated)
  • Large monorepos may need future incremental analysis optimization
  • 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, GitHub CopilotClaude Code, Codex, Gemini CLI, Cursor, VS Code, GitHub Copilot, Continue
Tools210