"Google Gemini" matching MCP servers:

Catch Gemini model upgrade regressions before they reach customers by running evals, comparing outputs, detecting regressions, and exporting audit receipts.

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.

MCP server for Mockzilla. Lets coding agents like Claude Code, Claude Desktop, Cursor and Gemini CLI install the Mockzilla CLI and run API mocks from an OpenAPI spec or a single endpoint. Log in from the agent to deploy hosted mocks on mockzilla.org

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.

Enables AI assistants to perform comprehensive code reviews of local uncommitted changes by combining git diffs with static analysis from linters like ESLint and TypeScript. Returns structured JSON feedback with findings, suggestions, and quality assessments powered by Google's Gemini CLI.

mcp-test-runner is an MCP server that lets your AI client (Claude / Cursor / Codex / Gemini) drive your entire QA loop end-to-end: * Run tests across pytest / Jest / Cypress / Go / Maestro — single MCP surface, one env var to switch * Analyze a URL (Web DOM probe) or a live mobile screen (Maestro hierarchy) to extract testable modules + candidate cases * Generate runna

Enables Claude to perform thorough code reviews by integrating with Codex and Gemini CLIs to provide senior-level feedback on code quality, security, performance, and best practices. Supports reviewing code snippets, individual files, or entire directories with automatic detection of available review tools.

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.

MCP server that gives AI coding assistants the ability to see and interact with mobile devices. 49 tools for Android/iOS — AI-powered visual analysis (Claude + Gemini), smart tap/type by description, Flutter widget tree inspection, video recording, and test script generation. 4-tier element search with <1ms local matching. Free tier included, zero setup via npx.

Enables AI agents to capture screenshots from Android devices and emulators, and manage connected devices for UI analysis and testing. Supports device listing, screenshot capture, and integrates with Claude Desktop, Gemini CLI, and GitHub Copilot.

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

Detect fabrication and hallucination in any LLM output. Score responses from GPT-4o, Claude, Gemini, Llama and 30+ models. Free tier included.

An MCP server that enforces unit testing standards by linting code and guiding agentic coding tools (like Gemini CLI or Claude Code) to follow best practices in test-driven development.

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.

A Model Context Protocol (MCP) server that analyzes software UI screenshots using Google's Gemini AI vision, providing detailed descriptions of UI elements, layout, functionality, and accessibility.

An MCP server that performs independent verification of artifacts against criteria using a different AI model lineage (codex, OpenAI, or Gemini) to catch defects that same-family checks might miss.

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.