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DimensionShrimp Task ManagerIntelligent task management for AI-powered development with chain-of-thought and reflection.MartinLoop MCP ServerAn independent control layer that gives AI coding agents budgets, brakes, and receipts
FMRS40 / 100 · D79 / 100 · B
Reliability8 / 2012 / 20
Security and permissions7 / 2018 / 20
Maintenance8 / 2016 / 20
Documentation7 / 2018 / 20
Setup experience10 / 2015 / 20
Best for
  • AI-assisted development requiring long-term project context.
  • Integration with MCP-compatible coding assistants like Claude Code and Cline.
  • Developers wanting structured task management to increase efficiency.
  • 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
  • Simple interactions that don't need task management.
  • Environments with strict security requirements for data location (you must configure DATA_DIR).
  • 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
  • File system access: needs to read/write task data files (specified by DATA_DIR).
  • Command execution: the MCP server is launched via command line, so the client must allow executing node commands.
  • 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
  • Data persistence: task data is stored locally; regular backup recommended.
  • Misconfiguration can prevent the server from starting.
  • Dependence on the MCP implementation of the AI client may cause compatibility issues.
  • 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, ClineClaude Code, Codex, Gemini CLI, Cursor, VS Code, GitHub Copilot, Continue
Tools60