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

DimensionPerfetto MCP ServerTurn natural language into powerful Perfetto trace analysisMartinLoop MCP ServerAn independent control layer that gives AI coding agents budgets, brakes, and receipts
FMRS63 / 100 · C79 / 100 · B
Reliability8 / 2012 / 20
Security and permissions14 / 2018 / 20
Maintenance12 / 2016 / 20
Documentation15 / 2018 / 20
Setup experience14 / 2015 / 20
Best for
  • Android developers analyzing Perfetto traces
  • Engineers who want jank, ANR, contention, and memory analysis without writing SQL
  • Clients supporting stdio MCP such as Cursor, Claude Code, VS Code, and Codex
  • 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 who do not analyze Perfetto traces
  • Scenarios where an absolute trace_path and process_name cannot be provided
  • Environments that cannot run Python MCP servers via uvx or pip
  • 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
  • Needs read access to local Perfetto trace files (absolute path passed as trace_path)
  • May download trace_processor_shell on first run (or use a local binary via PERFETTO_MCP_TRACE_PROCESSOR_BIN_PATH)
  • 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
  • Traces contain application and system runtime details; sharing them may expose sensitive information
  • Default behavior may download an external binary; restricted networks should configure a local path
  • Queries are generated by an LLM and results should be verified
  • 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 clientsCursor, Claude Code, VS Code, CodexClaude Code, Codex, Gemini CLI, Cursor, VS Code, GitHub Copilot, Continue
Tools120