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

DimensionOrangePro MCP ServerFind test gaps, generate grounded tests, and dynamically prove behavior with mutation testing.MartinLoop MCP ServerAn independent control layer that gives AI coding agents budgets, brakes, and receipts
FMRS75 / 100 · B79 / 100 · B
Reliability12 / 2012 / 20
Security and permissions18 / 2018 / 20
Maintenance14 / 2016 / 20
Documentation16 / 2018 / 20
Setup experience15 / 2015 / 20
Best for
  • Teams with medium-to-large TypeScript/JavaScript, Python, Go, or Java codebases wanting a deterministic, local-first testing workflow
  • Developers using MCP-compatible coding agents such as Claude Code, Cursor, Codex, Copilot, or OpenCode
  • Privacy-conscious teams: code never leaves the machine and keys stay in environment variables
  • 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 in Kotlin, Rust, PHP, C#, Ruby, Swift, C/C++ needing generated tests, runtime coverage, or dynamic proof (only static behavior extraction is supported for these)
  • Teams wanting hosted lifecycle management, cross-repo intelligence, or CI policy gates (this repo is the free local tool only)
  • Users who need test generation but won't configure a model key — generation requires BYOK
  • 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
  • Reads local repository files and git metadata to build the evidence graph
  • Writes reports and metadata to .orangepro/
  • Writes new generated tests under orangepro_generated/ (existing source files untouched)
  • Optionally reads OpenAI / Anthropic / Ollama credentials from env and sends grounded code context directly to your configured provider
  • 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
  • Generated tests land in orangepro_generated/ and should be reviewed before running
  • AI candidate links and flows are suggestions, never evidence; AI output does not change evidence tiers
  • opro generate --pr checks out a PR and mutates your working tree; prefer --base
  • With AI lanes enabled, grounded code context is sent directly to the configured model provider
  • The MCP server has local filesystem and command execution access to the repository — use only on trusted codebases
  • 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, Codex, Copilot / VS Code, OpenCode, Generic MCP clientsClaude Code, Codex, Gemini CLI, Cursor, VS Code, GitHub Copilot, Continue
Tools180