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

DimensionManaged Agents MCP ServerA local-first AI agent runtime with an MCP bridge.MartinLoop MCP ServerAn independent control layer that gives AI coding agents budgets, brakes, and receipts
FMRS44 / 100 · D79 / 100 · B
Reliability8 / 2012 / 20
Security and permissions8 / 2018 / 20
Maintenance7 / 2016 / 20
Documentation11 / 2018 / 20
Setup experience10 / 2015 / 20
Best for
  • Developers needing a local or self-hosted agent runtime
  • Teams requiring persistent sessions, auditability, and replay
  • Users working with DeepSeek Harness and MCP
  • 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 seeking a hosted model service
  • Users seeking a visual workflow builder
  • Environments without Node.js 22+ or a model-provider API key
  • 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
  • Access to the local runtime and its workspace state directory
  • Depending on configuration, local-process, Docker, Kubernetes, or self-hosted worker permissions
  • A configured model-provider API key for model execution
  • 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
  • Misconfigured sandbox backends may broaden tool access to the host or infrastructure
  • Credentials, files, memory, and audit data are stored in the runtime workspace or configured storage backends
  • After API-key authentication is enabled, key holders can make authorized runtime requests
  • 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 clientsDeepSeek HarnessClaude Code, Codex, Gemini CLI, Cursor, VS Code, GitHub Copilot, Continue
Tools00