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

DimensionEntrolyRecoverable, auditable context compression for AI agents.MartinLoop MCP ServerAn independent control layer that gives AI coding agents budgets, brakes, and receipts
FMRS67 / 100 · C79 / 100 · B
Reliability10 / 2012 / 20
Security and permissions14 / 2018 / 20
Maintenance13 / 2016 / 20
Documentation17 / 2018 / 20
Setup experience13 / 2015 / 20
Best for
  • Large repositories and document collections
  • Multi-turn, log-heavy AI agent sessions
  • Teams requiring evidence traceability, recovery, and audit records
  • Developers who want local processing and control over the model integration path
  • 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
  • Small projects or prompts already within budget
  • MCP-only setups that require automatic interception of every model request
  • Tasks that require the full context to remain visible at all times
  • Treating scoped benchmark results as guarantees across all models and production workloads
  • 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
  • Requires access to configured local project code, documents, logs, or other context data
  • MCP attachments can be scoped by project and grant scope, given an expiry, and revoked
  • Proxy mode requires the user to configure the relevant provider API key; Entroly does not choose the provider or receive its 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
  • Compression can omit relevant evidence; review Context Receipts and verification results
  • Exact recovery depends on retained receipts and the local recovery store; deleting that state removes the recovery path
  • MCP integrations do not automatically intercept every model request; provider savings require routing through the Entroly proxy
  • Unknown or ambiguous structures pass through unchanged, and unsafe overflow may produce HTTP 413
  • README benchmarks are scoped to particular datasets, budgets, models, and versions, not universal guarantees
  • 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 Desktop, Claude Code, Codex, OpenClaw, Cursor, Windsurf, VS Code MCP clients, Zed, GitHub Copilot CLIClaude Code, Codex, Gemini CLI, Cursor, VS Code, GitHub Copilot, Continue
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