"Multi-user production MCP server for Google Calendar and Sheets" matching MCP servers:

Enables Large Language Models to access and manipulate Autodesk Revit models through a pyRevit-based bridge and the Model Context Protocol.

An MCP server that queries multiple Ollama models and combines their responses, providing diverse AI perspectives on a single question for more comprehensive answers.

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

Gives LLM agents spatial awareness inside Autodesk Maya, enabling scene inspection and measurement, aesthetic and engineering audits, camera planning, checkpoint/rollback safety, asset import, and viewport or render previews. Agents can also execute arbitrary Python in Maya to build and verify 3D scenes against engineering rules instead of writing blind.

Compile, lint, simulate (60 Hz), and render headless 4-up 3D contact sheets from Three.js to GLB, USDZ, Android (Filament / Jetpack XR), iOS/visionOS (RealityKit), and WebXR.

Enables AI agents to invoke a local Stata installation, including a Windows Stata build under Wine on Linux and macOS, for regression analysis, econometrics, paper replication, and empirical research with command guards, resource monitoring, and automatic log capture.

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 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.

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.

Enable Claude (or any other LLM) to interactively debug your code (set breakpoints and evaluate expressions in stack frame). It's language-agnostic, assuming debugger console support and valid launch.json for debugging in VSCode.

Enables asynchronous and parallel execution of Claude Code tasks across multiple sessions, allowing users to start background tasks and continue working immediately without blocking.

MCP server that gives AI agents isolated, named Linux computers with stable IDs and lifecycle control. Supports multiple backends like Docker, Fly Machines, Modal, and E2B, with a dashboard for managing sandboxes.

Spawns multiple candidate reasoning paths concurrently, scores their progress against milestones, and halts underperforming branches early to cut inference costs.

A starter template for creating MCP servers that work with Puch AI, featuring ready-to-use tools for job searching and image processing. Includes examples for Bearer token authentication, OAuth integration with Google and GitHub, and demonstrates user-scoped data management.

Enables local, Docker-isolated code execution across six programming languages including Python, Rust, and TypeScript. It features pre-warmed container pooling, persistent sessions, and built-in support for machine learning libraries.

This read-only MCP Server allows you to connect to Google BigQuery data from Claude Desktop through CData JDBC Drivers. For full CRUD support, check out the first managed MCP platform: CData Connect AI (https://www.cdata.com/ai/).

A simple server that acts as a Master Control Program (MCP) for unified interaction with OpenAI and Anthropic (Claude) AI models through a single API endpoint.

Enables AI clients to interact with and control the Unity Editor through a Python MCP server bridge, allowing natural language-based Unity project manipulation.

A Docker-based FastMCP server for dynamic Python code execution with support for multiple MCP clients, automatic validation, runtime installation, and browser automation.

An MCP (Multi-Agent Conversation Protocol) Server that enables interaction with Google Workflows API, allowing management of workflow executions and definitions through natural language commands.

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.

Enables LLMs to drive Blender through socket-based two-way communication, letting them create and modify 3D objects, apply materials, run Blender Python, and fetch or generate assets while visually verifying results. Supports prompt-assisted 3D modeling, scene creation, and manipulation.

Enables Windows users to connect Antigravity CLI as an MCP subagent for coding tasks such as file reading, code execution, edits, and terminal commands, with model selection, conversation continuity, and streaming progress.

An MCP server that lets Large Language Models interact with Stata software to perform regression analysis and other statistical operations.

Enables Claude Desktop to control FreeCAD for 3D CAD modeling, including creating, editing, and deleting objects, executing Python code, and running FEM analyses.

An MCP server that grants AI agents unrestricted file system, Python, and PowerShell access on Windows for real, unfiltered automation.

An MCP server that enables running CLI for Microsoft 365 commands through GitHub Copilot Agent, allowing users to interact with Microsoft 365 services using natural language.

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 server that enables Claude Desktop to generate images using Google's Gemini AI models through the Model Context Protocol (MCP).

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.