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Turn Lighthouse audits into prioritized engineering backlogs with actionable acceptance criteria.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "lighthouse-mcp" yet — see the docs or source repo.
Please read this Lighthouse audit result and turn it into a development backlog ranked by impact and implementation effort. For each item, include evidence, recommended action, priority, suggested owner, and measurable acceptance criteria.
A prioritized performance improvement backlog that engineering teams can execute directly.
Using the Lighthouse report, break the required fixes into small tasks suitable for coding agents. For each task, specify target files or modules, implementation guidance, definition of done, and how to verify the fix.
A structured task list ready for AI coding agents or developers to handle item by item.
Based on this Lighthouse audit, create a pre-release quality checklist. Cover performance, accessibility, best practices, and SEO, and provide pass criteria and retest methods for each item.
A retestable, acceptance-ready pre-release checklist to help teams control launch quality.
Review code for security, quality, and performance issues with actionable suggestions.
Connect MCP agents to Lighter trading with safe, controlled execution.
Convert Lighthouse audits into fix packs for coding agents.
Audit web pages for WCAG issues and generate deterministic fixes and PRs.
Connect LightRAG through MCP for unified retrieval and knowledge QA integration.
Scan MCP server configs for injections, secrets, and dangerous commands.