"google trends" matching MCP servers:

Connects AI coding assistants to Gaffer test history and coverage data to analyze project health, debug failures, and identify untested code areas. It enables tools to track test stability, cluster failures by root cause, and monitor code coverage trends across projects.

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 local, stdio-only Model Context Protocol server that lets coding agents inspect, control, and test Apple iOS Simulators and Google Android Emulators. It exposes 29 typed tools for device lifecycle, app management, UI automation, screenshots, logs, permissions, location, and platform-specific test conditions.

WCAG-Compliance/wcagc-mcp lets an assistant run real axe-core accessibility scans through the user's own wcagc account, rather than guessing accessibility from markup it can see. Tools cover a single URL or PDF, a full-site crawl, saved multi-step journeys, and violation trends.

Provides AI assistants with token-efficient access to Google Play Android Vitals, enabling them to diagnose ANRs, track crashes, analyze startup performance, and compare app versions for release optimizations.

Build, sign, and publish iOS and Android apps through AI agents. Integrates Codemagic CI/CD, App Store Connect, and Google Play in one server.

Model Context Protocol (MCP) server for App Store Optimization. Score your App Store / Google Play listing metadata, check character limits, and clean up the iOS keyword field — right inside Claude, Cursor, or any MCP client.

Provides comprehensive website validation across performance, accessibility, SEO, and security dimensions using multiple testing services including WebPageTest, Google PageSpeed Insights, Axe DevTools, Mozilla Observatory, and SSL Labs. Enables automated website health assessments through browser automation and API integrations.

MCP server to mock OpenAI, Anthropic, and Google Gemini responses for testing AI integrations without real API keys or token spend.

Connect AI agents to your test results, insights, and targets. Query test runs, failures, flaky tests, and regressions across frameworks including Playwright, Jest, Pytest, Cypress and more.

Runs Google PageSpeed Insights audits against any public URL, returning Lighthouse scores, lab timing metrics, ranked fixes, and real-user Chrome UX Report field data.

Automate Google Play closed testing with AI - skip the hassle of finding testers and waiting 14+ days by telling your AI to handle it.

Panel Review is the guardian agent for AI's highest-stakes coding decisions. Before an agent's riskiest designs, diffs, or commits ship, four frontier models, from OpenAI, Anthropic, Google, and xAI, argue them through and return severity-tagged findings, with review gates the agent cannot silently skip.

A spec-compliant remote MCP server with built-in OAuth 2.1 and Dynamic Client Registration, enabling Notion Custom Agents to connect via 'Sign in with OAuth' without bearer tokens. It supports SSO federation to Google and Microsoft Entra, and includes basic tools like whoami, echo, and slow_task.

This MCP server builds a local flakiness knowledge graph from Playwright test run history and enables AI agents to query flaky tests, failure patterns, trends, and correlated git commits, helping diagnose test reliability without manual analysis.

Enables natural-language chat-driven API testing, letting users upload API specs, run deterministic pytest checks against live targets, inspect results, create defects, and view failure trends.

Provides deterministic, offline, sourced resolutions for 44 mobile game development problems spanning performance, memory, rendering, store policies, IAP billing, crash vitals, live-ops emergencies, and store-policy deadlines, along with pre-launch checklists and launch-day runbooks. It also statically audits project directories for Google Play and App Store compliance, including target SDK, 16 KB ELF alignment, privacy manifests, and secret-file exposure, without any network calls or shell execution.

Enables checking whether a Meta, LinkedIn, or Google Ads campaign is structurally able to serve and convert before spending, by inspecting schedule, bid, destination, approval, geo, and budget fields through read-only tools. It also reconciles reported spend across the three platforms against a ledger to surface discrepancies, armed campaigns, and drift.

Enables running the same prompt(s) across roughly 300 models from Anthropic, OpenAI, Google, Meta, Mistral, DeepSeek, Qwen and others, then comparing per-model outputs, latency, token usage, error rates and billed cost side by side. Supports free cost estimates before launching, asynchronous run creation with status polling and cancellation, prepaid x402 credit top-ups, and an optional AI-written comparison summary of the results.

A minimal MCP server built with NestJS to test PostHog MCP analytics integration, exposing mocked tools for trends and funnel analysis.