@sixty-sh/mcp
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- AlicenseAqualityCmaintenanceEnables AI coding agents to retrieve real-user performance metrics and 28-day field trends, run Lighthouse lab audits, and access remediation playbooks for LCP, INP, and CLS.7249 PyPIMIT
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TestChimp MCP Serverofficial
AlicenseNot gradedqualityBmaintenanceEnables coding agents to run QA using coverage signals, in-repo test plans, and release governance, and to call backend API endpoints through MCP tools.1,009 npmMIT- AlicenseNot gradedqualityBmaintenanceEnables agents to discover and configure model routing, delegate coding tasks with context files, scope restrictions, and verification, and resume existing sessions with delta instructions or review feedback.MIT
TDQS
Scored across 6 tools
Each tool targets a distinct phase of the finding lifecycle: list, view, claim, close, plus service health and installation. No overlap exists between the six tools.
All tool names follow a consistent verb_noun pattern in snake_case (list_findings, get_finding, claim_finding, close_finding, check_service, install_sixty). This is a model of uniform naming.
Six tools perfectly cover the core workflow of a performance-findings service: listing, inspecting, claiming, closing, plus setup and telemetry checks. None are redundant and none are missing.
The tool surface provides complete lifecycle coverage for findings (list, get, claim, close) and addresses operational needs (service health, installation). The only theoretical gap would be manual finding creation, which is outside the product's purpose since findings are auto-generated.