"Google Cloud Spanner" matching MCP servers:

Enables automation of Google Jules AI coding assistant through task creation, code review automation, repository management, and AI-powered development workflows. Supports multiple session modes including cloud deployment with persistent authentication.

A secure MCP server example that demonstrates how to deploy to Google Cloud Run with authentication and identity token protection. Serves as a tutorial template for building production-ready MCP servers in the cloud.

Enables MCP-compatible AI assistants to run Python code on Google Colab GPU/TPU runtimes, supporting accelerators like T4, A100, H100, with background execution and Google Drive integration.

Enables AI assistants to create and modify Google Apps Script projects, manage versions and deployments, run functions, and inspect execution history through natural language.

An advanced MCP server that provides an agentic interface to Google's Gemini 3.1 models via Vertex AI, combining real-time Google Search, URL analysis, and Python code execution to solve complex multi-step research and data tasks.

MCP server that enables cloud models (like Gemini/Claude) to delegate coding tasks to a local llama.cpp server, preserving cloud usage limits through an AI-powered code review loop.

MCP server connecting Claude Code with E2B cloud sandboxes for working on any GitHub repo.

An MCP server that enables AI agents to interact with Modal, allowing them to deploy apps and run functions in a serverless cloud environment.

A Model Context Protocol server that integrates Cursor IDE with Bitbucket Cloud, allowing developers to fetch repository information and commit data directly from their Bitbucket workspace.

Enables integration between SAP HANA Cloud Database and Cursor IDE through the Model Context Protocol, providing standardized interfaces for managing ML models and execution contexts.

Enables users to create, manage, and execute Google Apps Script projects through natural language. It provides comprehensive tools for code editing, function execution, deployment management, and monitoring script processes.

A comprehensive learning project demonstrating MCP server implementation with tools for calculator operations, file management, and system information retrieval, including Google ADK integration patterns and best practices.

A code-first MCP server that provides a single tool to execute JavaScript or TypeScript with authenticated access to Google Workspace APIs. It enables flexible interactions with services like Calendar and Drive by running user-provided scripts through a built-in runtime environment.

Lets any MCP-compatible agent use Google Colab or Jupyter runtimes as an execution backend, enabling code execution, notebook management, package installation, hardware introspection, training jobs, and file handling.

Provides integration with the Google Apps Script API, allowing management of script projects, deployments, versions, and executions through any MCP-compatible client like Claude Desktop or VS Code.

🗂️ A Model Context Protocol (MCP) server that provides integration with Turso databases for LLMs. This server implements a two-level authentication system to handle both organization-level and database-level operations, making it easy to manage and query Turso databases directly from LLMs.

Enables AI coding agents to manage cloud containers, create and edit files, run commands, and deploy projects directly.

Enables managing E2B cloud sandboxes, templates, filesystems, and processes through Model Context Protocol tools.

Enables seamless integration between MCP-compatible clients (like LM Studio) and Google Gemini API for image generation and multimodal tasks. Provides a hybrid local-cloud workflow combining local LM Studio execution with Gemini's cloud-powered image generation capabilities.

A secure, local communication runtime bridge that interfaces a cloud-based Large Language Model (Claude Desktop) with a local machine execution environment using the Model Context Protocol (MCP).