"Setting up Minecraft (MCP) servers with Python and Visual Studio Code" matching MCP servers:

Enables execution of Python code in a safe environment, including running scripts, installing packages, and retrieving variable values. Supports file operations and package management through pip.

An MCP server for securely executing Python code, supporting STDIO, Streamable HTTP, and SSE transports, with easy deployment on Heroku.

An MCP server for managing and operating Minecraft servers through multiple backend protocols including MCSManager API, RCON, and MSMP. It provides tools for instance lifecycle management, file operations, console commands, player administration, and server configuration with built-in security controls.

A client library that connects AI agents to Minecraft servers, providing full game control with 30 verified skills for common tasks including movement, combat, crafting, and building.

Enables AI agents to control Minecraft bots through over 30 verified skills including navigation, resource gathering, and advanced building. It allows for multi-bot management and seamless integration with MCP clients to automate complex in-game tasks.

Enables querying Minecraft Java server status through a remote MCP server deployed on Cloudflare Workers, with no authentication required.

Enables AI agents to control Minecraft bots via natural language commands by bridging a Python MCP server with a Node.js Mineflayer bridge. It supports a wide range of in-game actions including complex pathfinding, resource gathering, crafting, and combat.

A quickstart template to build and deploy a remote MCP server on Azure Functions using Python, secured with keys and HTTPS.

Connects AI agents to Minecraft servers via RCON to execute commands, monitor logs, and perform read-only SQLite database queries. It is specifically designed to facilitate AI-assisted plugin development, live debugging, and automated testing workflows.

A production-grade MCP server providing a persistent Python REPL with multi-session support, sandboxing, and timeout protection, enabling LLM agents to execute Python code across multiple turns with variables that persist between calls.

A Model Context Protocol server that allows LLMs to interact with Python environments, execute code, and manage files within a specified working directory.

Enables secure execution of Python code in a sandboxed WebAssembly environment using Pyodide and Deno. Automatically handles package management and captures complete execution results including stdout, stderr, and return values.

Enables LLM agents to play and survive in Minecraft by abstracting low-level tasks like pathfinding, building, and crafting into high-level transactional commands. It utilizes a "Helix" architecture to handle execution and coordinate math autonomously, allowing models to focus on strategy and high-level intent.

A Python template for creating MCP servers with embedded documentation, featuring example weather service tools using the NWS API.

A toolkit for managing Claude desktop app extension configurations, enabling features like Brave search, file operations, Git/GitHub integration, shell access, web scraping, HTTP requests, AWS documentation search, and Obsidian note management.

Connects AI assistants such as Cursor, ChatGPT, and Claude to Yatishara Studio, enabling secure access and interaction with the studio's capabilities through natural language.

Two-mode creative music studio for AI: scored composition (ABC notation with sheet music) and live performance (Strudel live coding with TidalCycles), with interactive UI rendering inline in Claude Desktop and other MCP clients.

An AI-driven data visualization and SQL chat platform that enables natural language to SQL conversion, interactive chart generation, and database querying through a comprehensive MCP interface. Supports multiple databases, intelligent chart recommendations, and secure data management with temporary link sharing.

Open-source MCP servers for ESG data extraction, analysis, and regulation management, providing 31 tools across 6 servers for tasks like metrics extraction, PDF processing, vector storage, and web scraping.

Visual icon search, retrieval, and comparison for AI agents. Search 200k+ icons semantically, render side-by-side comparison grids, and retrieve raw SVG markup — all tools return images so vision-capable LLMs can see the icons.