"A customizable and widely supported Minecraft server" matching MCP servers:

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.

Enables scaffolding complete Minecraft mod/plugin projects across Paper, Fabric, Forge, NeoForge, and Spigot version matrices, running Gradle builds via the wrapper, and consulting bundled development skills and API references. It covers Minecraft versions from 1.7.10 through 26.3 with matched JDK guidance.

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.

Enables Claude or Codex to build directly in a live Minecraft Java world via RCON, render textured previews so the AI can inspect its own work, place whole structures from ASCII layers, and hot-reload datapack minigames. It also moves worlds between the local server, bundled maps, and Realms-ready exports.

Relays a result screenshot to Slack so you can review a coding agent's output without opening the app.

Enables coding agents to add a bounded semantic-judgment layer for routing, ranking, extraction, verification, and escalation, returning typed signals and review recommendations.

Provides over 1,000 creative ways to decline requests across four categories (polite, humorous, professional, and creative). The MCP server wraps a REST API to help users craft professional rejections through natural language interactions.

A validation layer for AI coding assistants that enforces explicit LLM evaluations on plans, code diffs, and tests to ensure safer and higher-quality code.

Enables AI agents to break down complex tasks into manageable pieces using a structured JSON format with task tracking, context preservation, and progress monitoring capabilities.

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

An MCP Server that provides a conversational interface to the UK Open Banking account information API, allowing agents to interact with bank account data through natural language commands.

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.

Monitor failing GitHub Actions workflows, auto-fix them with OpenCode, and retry the run — driven by a workflow_run webhook, coordinated through an MCP server.

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

Enables searching and retrieving content, module information, and Twig template snippets from a-blog cms via its GET API.

A local, stdio-based MCP server that lets multiple coding agents share one project database for tasks, verification evidence, signals, knowledge, and conversation indexes. It enforces workflows with allowlisted verification runners and gate checks on acceptance criteria, evidence, dependencies, and high-risk approval before work can be closed.

Enables LLM clients such as Cursor and Claude to discover and use generated REST services through MCP tools for create, update, and delete actions and MCP resources for list and get-by-id context. Services generated in one command are exposed simultaneously as REST endpoints and MCP tools and resources.

Enables AI assistants to interact with generated REST APIs by discovering and using CRUD tools and read-only data resources.

Enables AI assistants to discover and invoke CRUD tools and read-only resources over the Model Context Protocol for generated API services.

MCP server for Redmine that enables interaction with issues, wiki pages, and time entries through natural language.

Enables AI assistants to interact directly with generated REST APIs by exposing CRUD operations as MCP tools and read-only data as resources.

Exposes generated CRUD services to LLM clients over the Model Context Protocol, providing tools for create, update, and delete actions plus read-only resources for listing and fetching records by id. It lets assistants like Claude, ChatGPT, and Cursor discover and manipulate the same data served by the project's REST endpoints without any extra glue code.

Exposes every generated CRUD service to LLM clients such as Claude, ChatGPT, or Cursor through discoverable MCP tools for create, update, and list actions plus read-only resources, so models can query and manipulate data without raw HTTP calls. It runs alongside the same codebase's REST endpoints, letting clients and AI share one data layer.

Enables LLMs to discover and invoke generated CRUD operations as MCP tools and read data through MCP resources, alongside standard REST endpoints, using one codebase.

Enables LLMs to discover and invoke generated CRUD tools and resources, allowing AI assistants to interact with the same data exposed by the REST API. Supports MCP clients such as Cursor and Claude over HTTP.

Enables LLMs to discover and invoke generated API actions as MCP tools and read context through MCP resources for list and get-by-id operations. It provides HTTP-based MCP access for clients such as Cursor and Claude without extra glue code.

Enables LLMs to interact directly with generated REST APIs by exposing CRUD actions as MCP tools and read-only data as MCP resources.

Enables LLMs and MCP clients to discover and use generated CRUD services through MCP tools and resources, exposing actions like create, update, delete, and read-only list/get access alongside REST endpoints.

Enables AI assistants to discover and invoke generated CRUD tools and read-only resources, letting them interact directly with REST-backed services built on Express, Mongoose, or Sequelize.

Enables LLMs and AI assistants to discover and use tools and resources for CRUD operations on generated services, providing direct interaction with the same data exposed by REST endpoints.

Enables LLMs to discover and invoke CRUD tools and read-only resources for generated services, allowing direct interaction with the same data exposed by the REST API.

Enables LLMs to interact with generated REST API services by exposing MCP tools and resources for CRUD operations, listing, and retrieval. It lets AI clients discover and call create, update, delete, list, and get-by-id actions against the same data available over REST.

Exposes every generated Express service to LLM clients over HTTP as MCP tools (create, update, delete actions) and resources (list and get-by-id context), so AI assistants can discover and manipulate application data without raw HTTP calls. This lets teams run a single codebase that serves both traditional REST clients and AI agents such as Cursor or Claude.

Enables LLMs to interact with generated CRUD services through MCP tools and resources, so they can create, update, list, and fetch records via a standard protocol. It also provides REST API access from the same codebase for traditional clients.

Enables LLM clients such as Claude, ChatGPT, and Cursor to discover and act on generated CRUD services over HTTP through tools like create, update, list, and delete, plus read-only resources for listing and fetching records by ID, with no extra glue code.

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.