"How to modify services in Google Cloud" matching MCP servers:

Inspect and manage IONOS CLOUD infrastructure via MCP

MCP server that exposes Google Jules AI agent as tools, allowing local AI agents to list authorized repositories and delegate coding tasks to Jules, receiving session URLs for tracking.

Enables finding files and knowing their location and permissions, organizing folders, moving and copying content, transferring files in and out, managing sharing with transparency, tracking changes, and handling shared drives.

Enables reading, searching, and writing to Google Chat spaces, direct messages, and sidebar through MCP clients such as Claude Code and Claude Desktop.

Provides access to Google Calendar, enabling listing calendars and events, checking availability, creating and updating events, and managing sharing through MCP.

Enables reading and writing spreadsheet ranges without destroying formulas, plus reshaping, formatting, and validating data within a spreadsheet.

Enables reading, editing, suggesting, and commenting on Google Docs from any MCP client, with scoped reads, minimal-diff edits, and support for tables, tabs, and layout.

Persistent, secure LXC sandbox environments for AI agents with native MCP support.

A Model Context Protocol server for Massdriver that enables AI assistants to manage infrastructure platform resources like projects, environments, deployments, policies, and more. It provides 106 tools and supports stdio or HTTP transports.

Enables AI assistants to manage and query Tiger Cloud database services, including service lifecycle operations, database connections, and SQL execution.

Provides access to your VictoriaTraces instance and seamless integration with VictoriaTraces APIs and documentation for querying traces, services, and operations.

Enables AI tools to perform real-time Google Search with grounded answers and inline citations, free with a Google account.

MCP server that provides 25 tools for AI agents to query and modify a dependency graph, enabling impact analysis and provenance tracking for AI-assisted development.

LLM Optimizer is an AI visibility intelligence platform. It analyzes how large language models and AI search engines perceive, cite, and recommend brands; then provides research-backed optimization strategies to improve that visibility.

Manages multiple development services with colored logs, filtering, and MCP integration for Claude Code.

The Multi DB MCP Server is a high-performance implementation of the Database Model Context Protocol designed to revolutionize how AI agents interact with databases. Currently supporting MySQL and PostgreSQL databases.

Keeps Jira Cloud, Jira Server, Linear or its own built-in tracker (plus Confluence pages) in one local SQLite file. Its MCP tools answer from that file: read-only SQL, full-text search across issues, comments and wiki pages, issue detail, sprint and retro reads.

Bitbucket Cloud MCP in Go: complete API auto-generated from spec, customizable prompts.

Orchestrates distributed research drones on Google Cloud Run, enabling scalable and bidirectional research task management.

Enables assistants to read account data (tunnels, usage, metrics, tokens, invoices, domains, notifications, cloud apps) and start/stop tunnels via the tunnels.io API and CLI.