"Google Chat" matching MCP servers:

Enables natural language queries of the Chrome UX Report API to fetch Core Web Vitals (LCP, INP, CLS, FCP, TTFB), compare form factors, benchmark pages against site averages, and analyze up to 40 weeks of performance trends.

An MCP server implementation for accessing Google Analytics 4 (GA4) data, built using the Model Context Protocol TypeScript SDK.

Provides tools and context for interacting with Google Cloud services, enabling natural language management of billing, monitoring, logging, IAM, Spanner, and more.

Enables AI assistants to query, search, and analyze logs across Google Cloud Platform projects. It supports advanced filtering by severity or resource type and provides detailed log entry retrieval and project listing capabilities.

Enables AI agents to query Google Analytics 4 data, including listing accounts and properties, running historical and real-time reports with customizable metrics and dimensions.

16-tool MCP server for Google PageSpeed Insights & Chrome UX Report APIs. Analyze, compare, and optimize web performance directly through Claude, Cursor, or any MCP-compatible AI client.

MCP server for measuring web performance with Google PageSpeed Insights, providing median scores with uncertainty and real-user data. It offers tools for scores, diagnostics, and comparisons to identify regressions.

A locally-hosted MCP (Model Context Protocol) server that gives Claude real tools to debug Docker containers — fetch logs, inspect memory/CPU, and run diagnostic commands inside a container, all from a chat with Claude Desktop.

A read-only MCP server that enables AI agents to act as GCP platform engineers, allowing them to investigate incidents, take inventory, and find cost-optimization opportunities in Google Cloud projects without mutating any infrastructure.

Analyzes local Claude Code logs to measure subscription value, waste, and rate-limit usage, including chat share and current limits, without uploading data.

Connects LLMs to Google PageSpeed Insights to analyze web performance, accessibility, SEO, and best practices, enabling AI assistants to audit and improve any web page.

An MCP server that monitors and provides analytics on weekly report submissions in a Google Sheet, allowing users to check missing submissions, view statistics, and track individual reporting status.

Enables MCP-capable AI clients to search ClickHouse logs, browse instances, databases, and tables, and inspect log histograms directly from a chat.

Lets your coding agent talk to the RunWhen platform — workspace chat, issues, SLXs, run sessions, and the Tool Builder — over the Model Context Protocol. Enables workspace chat with AI assistant, task authoring via Tool Builder, and direct data access to workspaces, issues, SLXs, run sessions, and more.

Lets an AI assistant inspect a running Google Chrome or Microsoft Edge browser over the Chrome DevTools Protocol, reading console output, network traffic, DOM snapshots, errors, performance metrics, storage, and screenshots. It also supports live event subscriptions, screen-frame streaming, and one-shot export of everything into an offline-readable archive such as HAR, CSV, and a self-contained HTML report.

An AI-powered server that provides rapid debugging of server logs with actionable fixes in under 30 seconds, featuring real-time monitoring and root cause analysis through Google Gemini integration.

Enables interaction with Google Cloud Platform services through gcloud CLI, supporting operations like querying logs, checking Cloud Run status, managing secrets, executing Cloud SQL queries, and monitoring billing information.

MCP server for Google Cloud Armor WAF log patrol. Enables daily_brief summaries of enforced denies, home-region false-positive checks, and preview rule review from Cloud Logging.

A lightweight, extensible MCP server for Splunk Enterprise that enables secure, async, chat-based interaction with Splunk data via Claude Desktop or any MCP-compatible agent.

Enables AI assistants to interact with and manage Google Cloud Platform resources including Compute Engine, Cloud Run, Storage, BigQuery, and other GCP services through a standardized MCP interface.