PageSpeed MCP Server

The PageSpeed MCP Server bridges the gap between conversational AI assistants and Google’s PageSpeed Insights, empowering developers to embed comprehensive web performance analysis directly into natural‑language workflows. By exposing a lightweight MCP endpoint, the server translates simple URL queries from an AI model into structured Lighthouse reports, returning rich metrics such as Core Web Vitals, best‑practice compliance, SEO health, and accessibility scores. This eliminates the need for developers to manually invoke the PageSpeed API or parse raw JSON, allowing assistants like Claude to interpret results and offer actionable insights in real time.

For developers building AI‑augmented tooling, the server’s value lies in its seamless integration with existing MCP toolchains. Once installed, a single command like can be issued within an AI conversation, and the assistant will respond with a concise summary of performance bottlenecks, along with targeted recommendations (e.g., image compression or render‑blocking script removal). This tight coupling reduces context switching, accelerates debugging cycles, and enables automated quality gates in CI/CD pipelines where an AI bot can flag regressions before a release.

Key capabilities are organized into four audit categories that mirror Lighthouse’s structure:

• Performance: Core Web Vitals (FCP, LCP, TTI, CLS), Speed Index, and network timing data.
• Best Practices: HTTPS enforcement, JavaScript error monitoring, console warning checks, and deprecated API usage.
• SEO: Meta tag validation, robots.txt parsing, structured data assessment, and mobile friendliness.
• Accessibility: ARIA attribute checks, color contrast analysis, heading hierarchy, alt text verification, and keyboard navigation support.

Each audit returns a detailed JSON payload that the AI can parse into natural‑language explanations, charts, or actionable steps. Developers can also tailor the analysis by specifying strategy (mobile/desktop), locale, and custom thresholds, allowing the server to serve both quick sanity checks and deep dives.

In real‑world scenarios, the PageSpeed MCP Server shines in continuous integration environments where an AI assistant monitors performance budgets across branches. It also supports rapid prototyping, letting designers query a mock URL and receive instant feedback on accessibility or SEO compliance. Because the server handles error scenarios—invalid URLs, API rate limits, and network timeouts—it offers a robust, production‑ready layer that abstracts away the complexities of interacting with Google’s API. Overall, this MCP server transforms routine performance checks into conversational, AI‑driven insights that accelerate development cycles and improve web quality.