"Most Used Minecraft Plugins (MCP)" matching MCP servers:

Lets coding agents search the official Obsidian directory of 8,900+ community plugins and 870+ themes, with download counts, latest versions and last-update dates, so they can check what already exists or spot gaps before writing code. It also works for picking a plugin or theme to install, needs no API key, and only reads public data.

Enables any MCP client such as Claude Desktop or Cursor to discover, search and inspect 50+ open-source DeepWhale DSH marketplace plugins, including version details, categories and install commands. It also checks which plugins are compatible with a given DSH runtime version, using a bundled offline snapshot when the remote index is unavailable.

A set of MCP servers that allow AI assistants to control a Minecraft server and client, including running commands, managing plugins, taking screenshots, and calling arbitrary API methods via reflection.

MCP server for managing AI skills and tools from GitHub marketplaces, enabling discovery, installation, removal, and auto-updates via natural language or commands.

Enables AI assistants to manage O2Switch hosting accounts, including deploying sites, managing subdomains, SSL certificates, WordPress, email, cron jobs, and more, with human confirmation for sensitive actions.

Provides a minimal OpenAI Plugin MCP server that exposes a read-only greeting tool over Streamable HTTP, useful for verifying local MCP connections and ChatGPT Work plugin integration.

A Model Context Protocol server that gives AI assistants native access to Minecraft mod development tools — decompile, remap, search, and analyze Minecraft source code directly from your AI workflow.

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.

MCP server for Forge Minecraft modding documentation. Gives AI assistants direct access to Forge docs with structured search results.

Enables local authoring and testing of Minecraft Java adventure maps through validated MCP tools, including structure building, snapshot/restore, and automated QA.

Enables Minecraft modpack development by generating FTB Quests chapters and tasks, KubeJS scripts (weapons, armor, recipes), validating SNBT/config files, and providing diagnostic checks.

MCP server that helps AI agents inspect Minecraft project evidence (crash logs, mod files, datapacks) before writing development code.

Model Context Protocol (MCP) stdio server built with the official MCP Python SDK (FastMCP). Exposes 3 MCP tools: package_capability, generate_dockerfile, generate_claude_desktop_config — package AIMarket capabilities as Docker images + MCP manifest + Claude Desktop config. Entrypoint: mcp_stdio_server.py; root Dockerfile + glama.json in repo.

This MCP server assists Minecraft Java plugin developers by providing dependency documentation lookups, version checking, and automated scanning for Gradle and Maven projects. It supports popular APIs such as Paper, Spigot, and LuckPerms to streamline plugin development and workspace analysis.

Provides API documentation browsing, code generation, and code review for Minecraft 1.21.1 Forge and NeoForge modding.

Connects ChatGPT Web to a self-hosted local coding workbench, enabling file editing, shell commands, Git/GitHub operations, multi-workspace management, code review, terminal processes, checkpoints, and optional Docker sandboxing.

Brings Visily designs into AI coding agents, enabling design-to-code generation, board discovery, and theme token application.

Provides tools for governed project work, including project setup, workspace management, and task execution, with credential-safe MCP wiring.

An MCP server that lets AI models drive any Coherent Gameface UI over Chrome DevTools Protocol, enabling JavaScript evaluation, screenshots, DOM inspection, console capture, and breakpoint debugging.

Turns a table your coding agent already has — a CSV, dataframe or semantic-model query result — into chart code that fits it first try, by profiling the data locally, ranking roughly 90 chart types by what it can honestly show, and returning verified D3, Plotly or matplotlib source you own and can run anywhere. It can also find the natural views inside a Microsoft Fabric semantic model and say which chart suits each.