"A query about Google Chrome or a related Chrome topic" matching MCP servers:

Enables coding agents to control and inspect a live Chrome browser via MCP, providing Chrome DevTools capabilities for automation, debugging, and performance analysis.

Enables querying real-user Core Web Vitals field measurements — 75th-percentile LCP, INP, and CLS with distributions and ~40 weeks of history — for any origin or page that has enough Chrome traffic.

Enables coding agents to control and inspect a live Chrome browser, providing reliable automation, debugging, performance insights, screenshots, network analysis, and console messages through MCP.

MCP server that lets coding agents control and inspect live Chrome browsers, providing full Chrome DevTools capabilities for automation, debugging, and performance analysis.

Enables read-only querying of Azure Log Analytics and Azure Resource Graph through MCP, supporting KQL queries, workspace discovery, and resource inventory exploration with Azure RBAC authentication.

Exposes a metrics query API to AI assistants, allowing them to issue queries and interact with the server's tools such as ping.

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 that provides cost and reliability observability for LLM and agent workflows. It records model calls and allows querying and aggregating telemetry data through MCP tools.

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

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.

Allows developers and AI Agents to query Google Cloud Logging using natural language, translating queries into Google Cloud Logging Query Language (LQL) with Vertex AI Gemini 2.5.

Enables AI agents to monitor Docker containers, system resources, ports, and logs in real-time.

Read-only MCP server for TrueNAS Scale debugging, providing k3s tools for kubectl operations and whitelisted midclt calls for system info, apps, and pools.

Enables autonomous AI agents to safely inspect, optimize, and manage live search campaigns through 38 purpose-built tools covering bids, budgets, keywords, RSAs, assets, and negative keyword harvesting. Bundles two-layer Pydantic execution shields with bounded bid ceilings and fixed stepping, a preflight gatekeeper, and W3C distributed tracing that separates upstream Google Ads API latency from local execution overhead.

Enables querying and searching logs from Kibana (ELK stack) via MCP, with support for project-based data views, trace ID correlation, and log expansion.

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.

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 the Chrome UX Report, providing real-user Core Web Vitals (LCP, INP, CLS) and historical trends for any origin or URL via natural language queries.

An MCP server for Grafana Loki that enables LLMs to query, tail, and analyze logs, featuring fuzzy container-name matching, compact output, and tools for log patterns, volume, and label discovery. It can run as a local stdio server or a containerized HTTP service.

Enables LLM agents to query real-time and historical analytics from WireBoard, allowing natural language questions about visitors, events, and site metrics.

Connects AI assistants to Crontinel, enabling natural language queries about cron jobs, queues, Horizon status, and alerts without opening a browser.

Query OpenTelemetry logs, traces and metrics from a self-hosted OTLP dashboard.

Enables AI agents to monitor and debug browser runtime errors, console logs, and page diagnostics in real time via a Chrome extension and local MCP server.

Enables LLMs to query telemetry data via the Spyglass AI agent, providing intelligent insights about application performance, errors, and bottlenecks.

Ask your AI agent about your MCP servers: which tools fail, how a release compares, what clients look for and do not find. Reads from mcpspan with a read token.

A read-only diagnostic server that inspects Linux PTP/Chrony status, PHC hardware-timestamping capabilities, and ROS 2 topic header timestamps to surface clock-domain mismatches, jitter, drift, and alignment problems in robotics systems. It exposes 15 tools and 4 prompts that generate traceable JSON or Markdown reports, running entirely locally over stdio without root access, cloud inference, or any clock modification.

Model Context Protocol (MCP) Server for Vunet vuSmartMaps - A multi-tenant observability platform integration. Query metrics, traces, logs, and data models from your Vunet tenants using natural language through AI assistants like Claude, GitHub Copilot, or any MCP-compatible client.

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Enables AI agents to query MQTT message history stored in SQLite, including topic inventories, last values, historical data, silent devices, and collector connection gaps. Supports publishing messages when write mode is enabled.