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

DimensionToolHiveRun any MCP server securely, instantly, anywhere.MartinLoop MCP ServerAn independent control layer that gives AI coding agents budgets, brakes, and receipts
FMRS37 / 100 · D79 / 100 · B
Reliability5 / 2012 / 20
Security and permissions7 / 2018 / 20
Maintenance10 / 2016 / 20
Documentation9 / 2018 / 20
Setup experience6 / 2015 / 20
Best for
  • Developers who want to run MCP servers quickly and securely
  • People who need MCP servers across multiple AI clients with consistency
  • Users who want to avoid manual configuration
  • 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
  • Developers who need to run MCP on servers without a GUI (CLI version may exist but not documented here)
  • Users needing Kubernetes-native MCP deployment (Operator mentioned but not documented)
  • 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
  • Network access to download MCP server images and communicate with clients
  • Container runtime to create and manage containers
  • Filesystem access for mounting directories for persistence
  • Secret management to securely store server credentials
  • 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
  • MCP servers may contain malicious code, but container isolation reduces risk
  • Security depends on container runtime configuration
  • Telemetry collects usage data but can be disabled in settings
  • 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 clientsGitHub Copilot, Cursor, Claude CodeClaude Code, Codex, Gemini CLI, Cursor, VS Code, GitHub Copilot, Continue
Tools00