"google trends" matching MCP servers:

Enables interaction with Google Ads through the Google Ads API using GCloud authentication. Supports GAQL query execution, performance data retrieval, account management, and resource discovery with pagination and multiple output formats.

An MCP server that enables management of Google Play games via the Google Games Management API, allowing automated interactions for game resets, hiding/unhiding data, and player management through natural language commands.

A Model Context Protocol server that connects Gemini CLI with CoinGecko's API, enabling users to access 46 cryptocurrency data tools including price tracking, market trends, and NFT information through terminal commands.

Aggregates multiple third-party APIs into unified MCP tools, providing out-of-the-box access to 10 popular services including OpenWeather, Google Maps, GitHub, Notion, Spotify, and more. Enables users to interact with weather data, search places, manage repositories, create content, and access various web services through a single MCP server.

Enables coding agents to discover, write, and test integrations for LinkedIn (Classic, Sales Navigator, Recruiter), WhatsApp, Instagram, Telegram, Gmail/Outlook/IMAP email, and Google/Outlook calendar by reading the live API contract and executing real calls on connected accounts.

An MCP server for API discovery and execution with a token-efficient search -> execute workflow over OpenAPI, Google Discovery, and optional native GraphQL and gRPC sources.

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.

A Flask-based MCP server designed for testing deployment on Google App Engine. Provides a deeplink checking endpoint that accepts flattened JSON parameters and forwards them as nested objects to external APIs.

An MCP server that provides access to the Test MCP Feb 5 API, enabling AI agents to interact with its endpoints through standardized tools. It supports seamless AI integration via the Model Context Protocol and is designed for easy deployment using Docker or Google Cloud Run.