A virtual travel robot environment based on the MCP server, allowing users to conduct virtual travel through Google Maps and interact with AI travelers.

The Local MCP Tools Collection aims to simplify the integration of multi - functional tools for local large language models, supporting multiple MCP servers through a single virtual environment, including web search, Python sandbox, and long - term memory functions.

A webpage summary agent tool based on mcp-agent and Qwen, which can run in the Windows environment. It can be used by creating a virtual environment with uv and configuring the API key.

An attempt to develop an MCP server for the Goose project, following its custom extension guide, supporting the creation of a Python virtual environment and running the MCP service through the uv command.

Implement the MCP service function for PC WeChat, and specify the Python virtual environment and script path through the configuration file

A simple MCP server project for simulating the raising of Tamagotchi, implemented based on Python and FastAPI, including virtual environment configuration and game operation functions.

Provide a virtual machine environment based on Magalu Cloud, enabling code execution and virtual resource interaction through the Model Context Protocol (MCP). Support the secure integration of LLMs with sandboxed VMs to enhance agent capabilities.

Project startup involves creating a virtual environment, synchronizing dependencies, and running a development server. Pay attention to code hot reload and API key management, and refer to other MCP service implementations.

venv-mcp-server is a service that solves the problem that LLMs cannot manage virtual environment dependencies reliably. It realizes the automatic dependency resolution and update of virtual environments through a tool list.

This is a Python project template that integrates code inspection and formatting tools such as ruff and black, uses pre-commit to manage hooks, includes the pytest testing framework and coverage plugin, and implements automated testing through Github Actions. It supports the devcontainer development environment and traditional virtual environments.

vCenter-mcp-server is an MCP server tool designed specifically for vCenter Server, providing virtual machine management, migration, and query functions to simplify operations in the virtualized environment.

LudusMCP is a model context protocol server for managing the Ludus laboratory environment based on natural language commands. It provides functions for deploying, configuring, and managing virtualized training environments and supports connecting to the Ludus server through WireGuard VPN or SSH tunnel.

This is a project configured with an MCP code runner server, supporting code execution in a container or virtual machine environment.

This project is used to create and manage MCP servers for ArcGIS services, providing step-by-step guides for initialization, virtual environment configuration, and dependency installation.

An MCP service project using a Python virtual environment, supporting the addition of functions through command-line tools, including developer tools and resource management capabilities.

Lilith Shell is an enhanced MCP server that allows AI assistants to execute commands in the terminal, providing security controls and testing capabilities. It should be used in a virtual machine or a resettable development environment due to security risks.

A multi - MCP server and client project integrating LangGraph pre - built ReAct agents, supporting multiple AI service APIs

The project is a Python-based MCP service, including server-side and client-side test code, managed using a virtual environment and the uv tool.

The Computer Use AI SDK developed by Screenpipe is an open - source project that provides an MCP server and client for controlling computer operations through AI. It supports the native macOS environment, does not require a virtual machine, can directly interact with any application or website, and provides basic functions such as launching applications, reading content, clicking, and entering text, aiming to build automated workflows and intelligent agents.

Create and configure the MSSQL development environment

This project is an MCP server based on the FastMCP framework, used to manage objects such as virtual servers, pools, and iRules of F5 devices through the iControl REST API, providing functions to create, update, list, and delete, and supporting environment variable configuration and Docker containerized deployment.

This project is a Python implementation of an MCP client interacting with the server, including the complete process of creating a virtual environment, configuring environment variables, and running client test file operations (such as writing and reading files).