"Finding businesses on Google that need a website" matching MCP servers:

Provides a remote coding environment for AI to publish static websites as live URLs, with live code editing and sandbox execution.

Provides agents with real Linux VMs to run commands, manage files, expose ports, and track costs, all through an ephemeral sandbox service.

A deployable MCP server for Cloudflare Workers or Azure Functions that provides example tools (time, echo, math), prompt templates for code assistance, and configuration resources. Enables AI assistants to interact with edge-deployed services through the Model Context Protocol.

An MCP Server that enables users to interact with Google's On-Demand Scanning API (v1beta1) through natural language, likely providing capabilities for vulnerability scanning and security analysis of containers and artifacts.

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

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.

Enables GUI automation by executing Python code with instrumented pyautogui, providing MCP-friendly output and inline screenshot delivery.

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/).

Provides a secure workspace for AI-driven file management and Python script execution designed to run on Vercel. It enables tools for full file operations and code execution within a sandboxed environment.

A server implementation for the Model Context Protocol (MCP) that runs on Cloudflare Workers and supports OAuth login, allowing Claude AI to use custom tools through local or remote connections.

Enables deployment of MCP servers on Cloudflare Workers with OAuth authentication and remote connectivity. Provides a template for creating cloud-hosted MCP servers that can be accessed by Claude Desktop and other MCP clients over HTTP/SSE.

A serverless deployment for Model Context Protocol (MCP) on Cloudflare Workers that enables AI agents to use custom tools without authentication requirements.

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.

A tool that allows deployment of a remote MCP (Model Context Protocol) server on Cloudflare Workers without authentication requirements, enabling connection to AI models through Claude Desktop or Cloudflare AI Playground.

Enables agents to accomplish multi-step work by writing a single sandboxed JavaScript program that drives shell, filesystem, HTTP, and every tool of any configured MCP server, returning only a small summary instead of raw JSON. This collapses dozens of advertised tool schemas into one tool, cutting per-request context by roughly 26× while keeping disabled upstream servers reachable.

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 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.

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.

Gives AI coding agents typed, mode-gated access to a real WordPress site — content, media, users and settings via core REST, plus PHP execution, SQL queries, filesystem operations and Elementor page read/build/patch/snapshot via a companion bridge plugin. Destructive actions and code execution are guarded by feature flags, explicit confirm literals, dry runs, redaction and audit logging.

A simple MCP server implementation in TypeScript that communicates over stdio, allowing users to ask questions that end with 'yes or no' to trigger the MCP tool in Cursor.

A self-hosted MCP server that enables AI coding agents to read, edit, search, and run code in local projects with human review loops and policy controls.

MCP-ORTools integrates Google's OR-Tools constraint programming solver with Large Language Models through the MCP, enabling AI models to: Submit and validate constraint models Set model parameters Solve constraint satisfaction and optimization problems Retrieve and analyze solution

Facilitates interaction with AWS Bedrock-enabled tools by implementing Anthropic's Model Context Protocol for seamless tool integration and communication.

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.

A Python code execution sandbox based on IPython and Docker. Stateful code execution, file transfer between host and container, configurable network access.

An MCP server for Task Trellis that provides tools for AI coding agents to manage tasks, currently featuring a simple hello_world demonstration tool.

An MCP server that enables AI applications to access 20+ model providers (including OpenAI, Anthropic, Google) through a unified interface for text and image generation.

A FastMCP server that turns JSON data into Plotly figures, deployable as an isolated service on Modal. Data goes in as JSON; a validated Plotly figure (JSON) or a rendered PNG comes back over the Model Context Protocol.