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

DimensionVictoriaMetrics MCP ServerOfficial VictoriaMetrics MCP server for seamless integration with VictoriaMetrics API and documentation.MartinLoop MCP ServerAn independent control layer that gives AI coding agents budgets, brakes, and receipts
FMRS69 / 100 · C79 / 100 · B
Reliability10 / 2012 / 20
Security and permissions15 / 2018 / 20
Maintenance16 / 2016 / 20
Documentation15 / 2018 / 20
Setup experience13 / 2015 / 20
Best for
  • Developers and SREs using VictoriaMetrics for monitoring and observability.
  • Engineers who want to leverage AI assistants to simplify metric queries and operations.
  • Teams needing quick access to documentation and troubleshooting guides.
  • 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 use VictoriaMetrics; this server is not suitable for other monitoring systems.
  • Scenarios requiring write or modify operations, as the server only supports read-only APIs.
  • Environments sensitive to resource consumption, as the embedded documentation vector database may increase memory and CPU usage.
  • 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
  • Read access to VictoriaMetrics instance APIs (query, list metrics, export data, etc.).
  • If using Cloud mode, access to VictoriaMetrics Cloud API key.
  • Network access to connect to the VictoriaMetrics instance or Cloud service may be required.
  • 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
  • Need to carefully manage API tokens to avoid leaking sensitive data.
  • AI-generated queries and configurations may contain errors; should be verified before use in production.
  • The server may consume significant resources, especially when loading the documentation vector database; can save resources by disabling the documentation tool.
  • 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, Cursor, Claude Code, Codex, VS Code, Zed, JetBrains IDEs, WindsurfClaude Code, Codex, Gemini CLI, Cursor, VS Code, GitHub Copilot, Continue
Tools300