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DimensionTestkube MCP ServerMCP server for the open testing platform built for AI-driven engineering teamsMartinLoop MCP ServerAn independent control layer that gives AI coding agents budgets, brakes, and receipts
FMRS63 / 100 · C79 / 100 · B
Reliability9 / 2012 / 20
Security and permissions13 / 2018 / 20
Maintenance15 / 2016 / 20
Documentation13 / 2018 / 20
Setup experience13 / 2015 / 20
Best for
  • Engineering teams already running Testkube on Kubernetes for automated testing
  • Platform and DevOps teams that want to manage test workflows and executions with AI assistants
  • Organizations looking to fold test result inspection and troubleshooting into AI workflows
  • 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 have not deployed Testkube or lack organization/environment credentials
  • Teams unwilling to expose a test access token to an AI client
  • General-purpose testing scenarios unrelated to Testkube or non-Kubernetes testing
  • 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 and use the Testkube access token (TK_ACCESS_TOKEN) for authentication
  • Access test workflows, executions, and artifacts within the specified Testkube organization and environment
  • Remote mode requires network access to https://api.testkube.io and the organization/environment 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
  • The access token is a sensitive credential; leaking it could let others read or act on test data in the target organization/environment
  • AI assistants may trigger or affect real test executions and the Kubernetes test resources they consume
  • The remote streamable-http mode sends requests and credentials to the Testkube cloud control plane
  • Overly broad token permissions or wrong organization/environment IDs could reach unintended environments
  • 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 DesktopClaude Code, Codex, Gemini CLI, Cursor, VS Code, GitHub Copilot, Continue
Tools00