Discover Awesome MCP Servers

Minecraft MCP Server

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.

dbt-cloud-migrate

Audits dbt Core projects for migration blockers and generates actionable guidance for migrating to dbt Cloud, including auto-fixing deprecated syntax.

MCP Perplexity Server

Provides AI-powered search, research, and reasoning capabilities through integration with Perplexity.ai, offering three specialized tools: general conversational AI, deep research with citations, and advanced reasoning.

MMA MCP Server

Enables users to search and query information about military service alternative companies in South Korea through the Military Manpower Administration (MMA) API. Supports filtering by service type, industry, company size, location, and recruitment status.

qmailing MCP server

Enables AI agents to manage email mailboxes, send and receive emails, and handle webhooks via qmailing.

Proton-MCP

MCP server for the Proton privacy suite — Mail, Pass, Drive, Calendar, and VPN. 36 tools for Claude and other MCP-compatible AI agents.

mcp-local-reader

Transform any local file into AI-optimized markdown format for seamless integration with Claude Desktop, Claude Code, and other MCP clients.

BitScale MCP Server

Connects your BitScale workspace to Claude, allowing you to manage grids, fetch row data, and trigger enrichment runs via natural language. It provides tools for listing grids, checking run status, and retrieving workspace details.

Perplexity MCP Server

Integrates Perplexity AI's search-enhanced language models with Claude Desktop, providing three tools with different complexity levels for quick fact-checking, technical analysis, and deep research.

magento-api-mcp

Enables searching and retrieving Magento 2 REST API documentation offline via local OpenAPI parsing, supporting endpoint search, schema lookup, and category browsing.

Nimiq MCP Server

A Model Context Protocol (MCP) server for interacting with the Nimiq blockchain.

Memory Crystal MCP Server

Enables AI agents to maintain persistent memory across sessions by capturing conversations, extracting durable knowledge, and injecting relevant context, supporting various MCP-compatible platforms.

Elnora MCP Server

Connects AI agents to the Elnora bioprotocol optimization platform, enabling generation, management, and optimization of wet-lab protocols through natural language.

PPTX Generator MCP Server

Generates professional PowerPoint presentations from Markdown with support for code blocks, tables, custom branding, and mixed formatting. Transforms lesson plans and documentation into styled PPTX files with syntax highlighting and customizable themes.

MyPlayground

Provides demo tools for addition, mock weather data, and username generation.

bq_mcp_server

A Python MCP server that retrieves and caches BigQuery metadata (datasets, tables, columns) and enables secure SQL query execution with cost control, file export, and keyword search.

A MCP server for Godot RAG

Este servidor MCP é usado para fornecer documentação do Godot ao modelo RAG do Godot.

discord-mcp-server

Lets any MCP-compatible AI client interact with Discord — send messages, manage channels, create webhooks, assign roles, and more.

SwiftOpenAI MCP Server

A universal server that enables MCP-compatible clients (like Claude Desktop, Cursor, VS Code) to access OpenAI's APIs for chat completions, image generation, embeddings, and model listing through a standardized interface.

Cars MCP Server

Okay, here's a basic example of how you might set up a simple Minecraft Protocol (MCP) server using Spring AI concepts. Keep in mind that this is a *very* high-level outline. Building a full MCP server is a complex undertaking. This example focuses on illustrating how Spring AI *could* be integrated for certain aspects, not on providing a complete, production-ready server. **Conceptual Overview** The core idea is to use Spring AI to handle certain aspects of the server logic, such as: * **Natural Language Command Processing:** Allow players to issue commands in natural language, which Spring AI can then translate into specific server actions. * **Dynamic Content Generation:** Use AI to generate quests, stories, or even world elements on the fly. * **NPC Behavior:** Control the behavior of non-player characters (NPCs) using AI models. **Simplified Example (Focusing on Command Processing)** Let's focus on the command processing aspect for this example. **1. Project Setup (Maven/Gradle)** You'll need a Spring Boot project. Here's a basic `pom.xml` (Maven) with the necessary dependencies: ```xml <?xml version="1.0" encoding="UTF-8"?> <project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 https://maven.apache.org/xsd/maven-4.0.0.xsd"> <modelVersion>4.0.0</modelVersion> <parent> <groupId>org.springframework.boot</groupId> <artifactId>spring-boot-starter-parent</artifactId> <version>3.2.0</version> <!-- Use the latest Spring Boot version --> <relativePath/> <!-- lookup parent from repository --> </parent> <groupId>com.example</groupId> <artifactId>mcp-server</artifactId> <version>0.0.1-SNAPSHOT</version> <name>mcp-server</name> <description>Basic MCP Server with Spring AI</description> <properties> <java.version>17</java.version> <spring-ai.version>1.0.0-M2</spring-ai.version> <!-- Use the latest Spring AI version --> </properties> <dependencies> <dependency> <groupId>org.springframework.boot</groupId> <artifactId>spring-boot-starter</artifactId> </dependency> <dependency> <groupId>org.springframework.boot</groupId> <artifactId>spring-boot-starter-test</artifactId> <scope>test</scope> </dependency> <!-- Spring AI Dependencies --> <dependency> <groupId>org.springframework.ai</groupId> <artifactId>spring-ai-core</artifactId> <version>${spring-ai.version}</version> </dependency> <dependency> <groupId>org.springframework.ai</groupId> <artifactId>spring-ai-openai</artifactId> <version>${spring-ai.version}</version> </dependency> <!-- Netty for MCP Communication (Example) --> <dependency> <groupId>io.netty</groupId> <artifactId>netty-all</artifactId> <version>4.1.100.Final</version> <!-- Use the latest Netty version --> </dependency> <!-- Lombok for boilerplate code reduction --> <dependency> <groupId>org.projectlombok</groupId> <artifactId>lombok</artifactId> <optional>true</optional> </dependency> <dependency> <groupId>org.springframework.boot</groupId> <artifactId>spring-boot-configuration-processor</artifactId> <optional>true</optional> </dependency> </dependencies> <build> <plugins> <plugin> <groupId>org.springframework.boot</groupId> <artifactId>spring-boot-maven-plugin</artifactId> <configuration> <excludes> <exclude> <groupId>org.projectlombok</groupId> <artifactId>lombok</artifactId> </exclude> </excludes> </configuration> </plugin> </plugins> </build> <repositories> <repository> <id>spring-milestones</id> <name>Spring Milestones</name> <url>https://repo.spring.io/milestone</url> <snapshots> <enabled>false</enabled> </snapshots> </repository> </repositories> </project> ``` **Important:** * Replace `3.2.0` and `1.0.0-M2` with the latest stable versions of Spring Boot and Spring AI, respectively. * You'll need an OpenAI API key. Set it as an environment variable or in your `application.properties` file. * This example uses Netty for handling the network communication. You could use other libraries as well. **2. `application.properties` (or `application.yml`)** ```properties spring.ai.openai.api-key=YOUR_OPENAI_API_KEY ``` **3. MCP Server (Simplified with Netty)** ```java package com.example.mcpserver; import io.netty.bootstrap.ServerBootstrap; import io.netty.channel.*; import io.netty.channel.nio.NioEventLoopGroup; import io.netty.channel.socket.SocketChannel; import io.netty.channel.socket.nio.NioServerSocketChannel; import io.netty.handler.codec.string.StringDecoder; import io.netty.handler.codec.string.StringEncoder; import lombok.RequiredArgsConstructor; import org.springframework.ai.client.AiClient; import org.springframework.ai.prompt.PromptTemplate; import org.springframework.beans.factory.annotation.Value; import org.springframework.boot.CommandLineRunner; import org.springframework.boot.SpringApplication; import org.springframework.boot.autoconfigure.SpringBootApplication; import org.springframework.context.annotation.Bean; @SpringBootApplication public class McpServerApplication { public static void main(String[] args) { SpringApplication.run(McpServerApplication.class, args); } @Bean public CommandLineRunner run(McpServer mcpServer) { return args -> { mcpServer.start(); }; } @Bean public McpServer mcpServer(AiClient aiClient, @Value("${server.port:25565}") int port) { return new McpServer(aiClient, port); } } @RequiredArgsConstructor class McpServer { private final AiClient aiClient; private final int port; public void start() throws Exception { EventLoopGroup bossGroup = new NioEventLoopGroup(); EventLoopGroup workerGroup = new NioEventLoopGroup(); try { ServerBootstrap b = new ServerBootstrap(); b.group(bossGroup, workerGroup) .channel(NioServerSocketChannel.class) .childHandler(new ChannelInitializer<SocketChannel>() { @Override public void initChannel(SocketChannel ch) { ChannelPipeline p = ch.pipeline(); p.addLast(new StringDecoder(), new StringEncoder(), new McpServerHandler(aiClient)); } }) .option(ChannelOption.SO_BACKLOG, 128) .childOption(ChannelOption.SO_KEEPALIVE, true); // Bind and start to accept incoming connections. ChannelFuture f = b.bind(port).sync(); System.out.println("MCP Server started on port " + port); // Wait until the server socket is closed. // In this example, this does not happen, but you can do that to gracefully // shut down your server. f.channel().closeFuture().sync(); } finally { workerGroup.shutdownGracefully(); bossGroup.shutdownGracefully(); } } } @RequiredArgsConstructor class McpServerHandler extends ChannelInboundHandlerAdapter { private final AiClient aiClient; @Override public void channelRead(ChannelHandlerContext ctx, Object msg) { String command = (String) msg; System.out.println("Received command: " + command); // Use Spring AI to process the command String aiResponse = processCommand(command); // Send the response back to the client ctx.writeAndFlush(aiResponse + "\n"); } private String processCommand(String command) { // Define a prompt template for command processing String promptString = "You are a Minecraft server assistant. The player said: {command}. Determine the appropriate Minecraft command and explain it to the user. If the command is not valid, respond with an error message."; PromptTemplate promptTemplate = new PromptTemplate(promptString); // Create a prompt with the player's command org.springframework.ai.prompt.Prompt prompt = promptTemplate.create(org.springframework.ai.prompt.PromptTemplate.map("command", command)); // Call the AI model String aiResponse = aiClient.generate(prompt).getGeneration().getText(); return aiResponse; } @Override public void exceptionCaught(ChannelHandlerContext ctx, Throwable cause) { cause.printStackTrace(); ctx.close(); } } ``` **Explanation:** 1. **Dependencies:** The `pom.xml` includes Spring AI, Netty, and Lombok. 2. **`application.properties`:** Sets the OpenAI API key. 3. **`McpServerApplication`:** The main Spring Boot application class. It creates the `McpServer` bean and starts it when the application runs. 4. **`McpServer`:** This class uses Netty to create a simple TCP server. It listens for incoming connections on the specified port. 5. **`McpServerHandler`:** This class handles incoming messages (commands) from clients. * It receives the command as a string. * It uses Spring AI's `AiClient` to process the command. * It sends the AI-generated response back to the client. 6. **`processCommand`:** * Defines a prompt template that instructs the AI model to act as a Minecraft server assistant. * Creates a `Prompt` object with the player's command. * Calls the `AiClient` to generate a response based on the prompt. **How it Works:** 1. The server starts and listens for connections. 2. A player connects to the server. 3. The player sends a command (e.g., "I want to build a house"). 4. The `McpServerHandler` receives the command. 5. The `processCommand` method constructs a prompt for the AI model, including the player's command. 6. The `AiClient` sends the prompt to the OpenAI API. 7. The OpenAI API generates a response (e.g., "To build a house, you'll need wood, stone, and a crafting table. The command to get wood is `/give @p minecraft:oak_log 64`"). 8. The `McpServerHandler` sends the AI-generated response back to the player. **To Run:** 1. Make sure you have Java 17 or later installed. 2. Set the `spring.ai.openai.api-key` property in `application.properties` with your OpenAI API key. 3. Run the Spring Boot application. 4. Use a simple TCP client (like `netcat` or a custom client) to connect to the server on the specified port (default 25565). 5. Send commands to the server. **Important Considerations:** * **Security:** This is a *very* basic example and does not include any security measures. In a real-world MCP server, you would need to implement proper authentication, authorization, and input validation to prevent malicious attacks. * **MCP Protocol:** This example doesn't implement the full Minecraft Protocol. You would need to handle the protocol handshake, packet encoding/decoding, and other protocol-specific details. Libraries like `mc-netty` can help with this. * **Error Handling:** The error handling in this example is minimal. You should add more robust error handling to catch exceptions and provide informative error messages to the player. * **AI Model Cost:** Using OpenAI's API can incur costs. Be mindful of your usage and set up billing alerts. * **Prompt Engineering:** The quality of the AI's responses depends heavily on the prompt you provide. Experiment with different prompts to get the desired behavior. * **Rate Limiting:** The OpenAI API has rate limits. Implement rate limiting in your server to avoid exceeding these limits. * **Context Management:** For more complex interactions, you'll need to manage the context of the conversation with the player. This could involve storing the player's inventory, location, and other relevant information. **Further Development:** * **Implement the full MCP protocol:** Use a library like `mc-netty` to handle the protocol details. * **Add more AI-powered features:** * Dynamic quest generation. * NPC behavior control. * World generation. * **Improve the command processing:** * Add support for more complex commands. * Implement command validation. * Provide more helpful feedback to the player. * **Integrate with a Minecraft server API:** If you want to modify the game world directly, you'll need to integrate with a Minecraft server API like Bukkit or Spigot. **In Portuguese (Translation):** Aqui está um exemplo básico de como você pode configurar um servidor Minecraft Protocol (MCP) simples usando conceitos do Spring AI. Lembre-se de que este é um esboço *muito* geral. Construir um servidor MCP completo é uma tarefa complexa. Este exemplo se concentra em ilustrar como o Spring AI *poderia* ser integrado para certos aspectos, não em fornecer um servidor completo e pronto para produção. **Visão Geral Conceitual** A ideia central é usar o Spring AI para lidar com certos aspectos da lógica do servidor, como: * **Processamento de Comandos em Linguagem Natural:** Permitir que os jogadores emitam comandos em linguagem natural, que o Spring AI pode então traduzir em ações específicas do servidor. * **Geração Dinâmica de Conteúdo:** Usar IA para gerar missões, histórias ou até mesmo elementos do mundo em tempo real. * **Comportamento de NPCs:** Controlar o comportamento de personagens não jogáveis (NPCs) usando modelos de IA. **Exemplo Simplificado (Focando no Processamento de Comandos)** Vamos nos concentrar no aspecto do processamento de comandos para este exemplo. **1. Configuração do Projeto (Maven/Gradle)** Você precisará de um projeto Spring Boot. Aqui está um `pom.xml` básico (Maven) com as dependências necessárias: ```xml <?xml version="1.0" encoding="UTF-8"?> <project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 https://maven.apache.org/xsd/maven-4.0.0.xsd"> <modelVersion>4.0.0</modelVersion> <parent> <groupId>org.springframework.boot</groupId> <artifactId>spring-boot-starter-parent</artifactId> <version>3.2.0</version> <!-- Use a versão mais recente do Spring Boot --> <relativePath/> <!-- lookup parent from repository --> </parent> <groupId>com.example</groupId> <artifactId>mcp-server</artifactId> <version>0.0.1-SNAPSHOT</version> <name>mcp-server</name> <description>Basic MCP Server with Spring AI</description> <properties> <java.version>17</java.version> <spring-ai.version>1.0.0-M2</spring-ai.version> <!-- Use a versão mais recente do Spring AI --> </properties> <dependencies> <dependency> <groupId>org.springframework.boot</groupId> <artifactId>spring-boot-starter</artifactId> </dependency> <dependency> <groupId>org.springframework.boot</groupId> <artifactId>spring-boot-starter-test</artifactId> <scope>test</scope> </dependency> <!-- Spring AI Dependencies --> <dependency> <groupId>org.springframework.ai</groupId> <artifactId>spring-ai-core</artifactId> <version>${spring-ai.version}</version> </dependency> <dependency> <groupId>org.springframework.ai</groupId> <artifactId>spring-ai-openai</artifactId> <version>${spring-ai.version}</version> </dependency> <!-- Netty for MCP Communication (Example) --> <dependency> <groupId>io.netty</groupId> <artifactId>netty-all</artifactId> <version>4.1.100.Final</version> <!-- Use a versão mais recente do Netty --> </dependency> <!-- Lombok for boilerplate code reduction --> <dependency> <groupId>org.projectlombok</groupId> <artifactId>lombok</artifactId> <optional>true</optional> </dependency> <dependency> <groupId>org.springframework.boot</groupId> <artifactId>spring-boot-configuration-processor</artifactId> <optional>true</optional> </dependency> </dependencies> <build> <plugins> <plugin> <groupId>org.springframework.boot</groupId> <artifactId>spring-boot-maven-plugin</artifactId> <configuration> <excludes> <exclude> <groupId>org.projectlombok</groupId> <artifactId>lombok</artifactId> </exclude> </excludes> </configuration> </plugin> </plugins> </build> <repositories> <repository> <id>spring-milestones</id> <name>Spring Milestones</name> <url>https://repo.spring.io/milestone</url> <snapshots> <enabled>false</enabled> </snapshots> </repository> </repositories> </project> ``` **Importante:** * Substitua `3.2.0` e `1.0.0-M2` pelas versões estáveis mais recentes do Spring Boot e Spring AI, respectivamente. * Você precisará de uma chave de API do OpenAI. Defina-a como uma variável de ambiente ou no seu arquivo `application.properties`. * Este exemplo usa Netty para lidar com a comunicação de rede. Você pode usar outras bibliotecas também. **2. `application.properties` (ou `application.yml`)** ```properties spring.ai.openai.api-key=SUA_CHAVE_API_OPENAI ``` **3. Servidor MCP (Simplificado com Netty)** ```java package com.example.mcpserver; import io.netty.bootstrap.ServerBootstrap; import io.netty.channel.*; import io.netty.channel.nio.NioEventLoopGroup; import io.netty.channel.socket.SocketChannel; import io.netty.channel.socket.nio.NioServerSocketChannel; import io.netty.handler.codec.string.StringDecoder; import io.netty.handler.codec.string.StringEncoder; import lombok.RequiredArgsConstructor; import org.springframework.ai.client.AiClient; import org.springframework.ai.prompt.PromptTemplate; import org.springframework.beans.factory.annotation.Value; import org.springframework.boot.CommandLineRunner; import org.springframework.boot.SpringApplication; import org.springframework.boot.autoconfigure.SpringBootApplication; import org.springframework.context.annotation.Bean; @SpringBootApplication public class McpServerApplication { public static void main(String[] args) { SpringApplication.run(McpServerApplication.class, args); } @Bean public CommandLineRunner run(McpServer mcpServer) { return args -> { mcpServer.start(); }; } @Bean public McpServer mcpServer(AiClient aiClient, @Value("${server.port:25565}") int port) { return new McpServer(aiClient, port); } } @RequiredArgsConstructor class McpServer { private final AiClient aiClient; private final int port; public void start() throws Exception { EventLoopGroup bossGroup = new NioEventLoopGroup(); EventLoopGroup workerGroup = new NioEventLoopGroup(); try { ServerBootstrap b = new ServerBootstrap(); b.group(bossGroup, workerGroup) .channel(NioServerSocketChannel.class) .childHandler(new ChannelInitializer<SocketChannel>() { @Override public void initChannel(SocketChannel ch) { ChannelPipeline p = ch.pipeline(); p.addLast(new StringDecoder(), new StringEncoder(), new McpServerHandler(aiClient)); } }) .option(ChannelOption.SO_BACKLOG, 128) .childOption(ChannelOption.SO_KEEPALIVE, true); // Bind and start to accept incoming connections. ChannelFuture f = b.bind(port).sync(); System.out.println("Servidor MCP iniciado na porta " + port); // Wait until the server socket is closed. // In this example, this does not happen, but you can do that to gracefully // shut down your server. f.channel().closeFuture().sync(); } finally { workerGroup.shutdownGracefully(); bossGroup.shutdownGracefully(); } } } @RequiredArgsConstructor class McpServerHandler extends ChannelInboundHandlerAdapter { private final AiClient aiClient; @Override public void channelRead(ChannelHandlerContext ctx, Object msg) { String command = (String) msg; System.out.println("Comando recebido: " + command); // Use Spring AI to process the command String aiResponse = processCommand(command); // Send the response back to the client ctx.writeAndFlush(aiResponse + "\n"); } private String processCommand(String command) { // Define a prompt template for command processing String promptString = "Você é um assistente de servidor Minecraft. O jogador disse: {command}. Determine o comando Minecraft apropriado e explique-o ao usuário. Se o comando não for válido, responda com uma mensagem de erro."; PromptTemplate promptTemplate = new PromptTemplate(promptString); // Create a prompt with the player's command org.springframework.ai.prompt.Prompt prompt = promptTemplate.create(org.springframework.ai.prompt.PromptTemplate.map("command", command)); // Call the AI model String aiResponse = aiClient.generate(prompt).getGeneration().getText(); return aiResponse; } @Override public void exceptionCaught(ChannelHandlerContext ctx, Throwable cause) { cause.printStackTrace(); ctx.close(); } } ``` **Explicação:** 1. **Dependências:** O `pom.xml` inclui Spring AI, Netty e Lombok. 2. **`application.properties`:** Define a chave de API do OpenAI. 3. **`McpServerApplication`:** A classe principal da aplicação Spring Boot. Ela cria o bean `McpServer` e o inicia quando a aplicação é executada. 4. **`McpServer`:** Esta classe usa Netty para criar um servidor TCP simples. Ele escuta as conexões de entrada na porta especificada. 5. **`McpServerHandler`:** Esta classe lida com as mensagens de entrada (comandos) dos clientes. * Ele recebe o comando como uma string. * Ele usa o `AiClient` do Spring AI para processar o comando. * Ele envia a resposta gerada pela IA de volta ao cliente. 6. **`processCommand`:** * Define um modelo de prompt que instrui o modelo de IA a atuar como um assistente de servidor Minecraft. * Cria um objeto `Prompt` com o comando do jogador. * Chama o `AiClient` para gerar uma resposta com base no prompt. **Como Funciona:** 1. O servidor inicia e escuta as conexões. 2. Um jogador se conecta ao servidor. 3. O jogador envia um comando (por exemplo, "Eu quero construir uma casa"). 4. O `McpServerHandler` recebe o comando. 5. O método `processCommand` constrói um prompt para o modelo de IA, incluindo o comando do jogador. 6. O `AiClient` envia o prompt para a API do OpenAI. 7. A API do OpenAI gera uma resposta (por exemplo, "Para construir uma casa, você precisará de madeira, pedra e uma mesa de trabalho. O comando para obter madeira é `/give @p minecraft:oak_log 64`"). 8. O `McpServerHandler` envia a resposta gerada pela IA de volta ao jogador. **Para Executar:** 1. Certifique-se de ter o Java 17 ou posterior instalado. 2. Defina a propriedade `spring.ai.openai.api-key` em `application.properties` com sua chave de API do OpenAI. 3. Execute a aplicação Spring Boot. 4. Use um cliente TCP simples (como `netcat` ou um cliente personalizado) para se conectar ao servidor na porta especificada (padrão 25565). 5. Envie comandos para o servidor. **Considerações Importantes:** * **Segurança:** Este é um exemplo *muito* básico e não inclui nenhuma medida de segurança. Em um servidor MCP real, você precisaria implementar autenticação, autorização e validação de entrada adequadas para evitar ataques maliciosos. * **Protocolo MCP:** Este exemplo não implementa o protocolo Minecraft completo. Você precisaria lidar com o handshake do protocolo, codificação/decodificação de pacotes e outros detalhes específicos do protocolo. Bibliotecas como `mc-netty` podem ajudar com isso. * **Tratamento de Erros:** O tratamento de erros neste exemplo é mínimo. Você deve adicionar um tratamento de erros mais robusto para capturar exceções e fornecer mensagens de erro informativas ao jogador. * **Custo do Modelo de IA:** O uso da API do OpenAI pode gerar custos. Esteja atento ao seu uso e configure alertas de faturamento. * **Engenharia de Prompt:** A qualidade das respostas da IA depende muito do prompt que você fornece. Experimente diferentes prompts para obter o comportamento desejado. * **Limitação de Taxa:** A API do OpenAI tem limites de taxa. Implemente a limitação de taxa em seu servidor para evitar exceder esses limites. * **Gerenciamento de Contexto:** Para interações mais complexas, você precisará gerenciar o contexto da conversa com o jogador. Isso pode envolver o armazenamento do inventário, localização e outras informações relevantes do jogador. **Desenvolvimento Adicional:** * **Implemente o protocolo MCP completo:** Use uma biblioteca como `mc-netty` para lidar com os detalhes do protocolo. * **Adicione mais recursos alimentados por IA:** * Geração dinâmica de missões. * Controle do comportamento de NPCs. * Geração de mundo. * **Melhore o processamento de comandos:** * Adicione suporte para comandos mais complexos. * Implemente a validação de comandos. * Forneça feedback mais útil ao jogador. * **Integre com uma API de servidor Minecraft:** Se você quiser modificar o mundo do jogo diretamente, precisará se integrar a uma API de servidor Minecraft como Bukkit ou Spigot. This provides a starting point. Remember to adapt and expand upon this example to create a more complete and functional MCP server. Good luck!

mcp-jenkins

A integração do Jenkins com o Protocolo de Contexto do Modelo (MCP) é uma implementação de código aberto que conecta o Jenkins com modelos de linguagem de IA seguindo a especificação MCP da Anthropic. Este projeto permite interações de IA seguras e contextuais com ferramentas do Jenkins, mantendo a privacidade e a segurança dos dados.

FFmpeg MCP

Enables video and audio processing through FFmpeg, supporting format conversion, compression, trimming, audio extraction, frame extraction, video merging, and subtitle burning through natural language commands.

MCP Server for Odoo

Enables AI assistants to interact with Odoo ERP systems through natural language, allowing users to search, create, update, and manage business records like customers, products, and invoices across any Odoo instance.

BestReads MCP Server

Enables personalized book recommendations by managing reading profiles and preferences, with tools to add genres, authors, and track books, then get AI-powered suggestions.

Tiger MCP

Enables trading and market analysis through Tiger Brokers API integration. Provides real-time market data, portfolio management, order execution, and technical analysis tools with a comprehensive web dashboard for monitoring.

Commodore 64 Ultimate MCP Server

Enables AI assistants to control Commodore 64 Ultimate hardware via REST API, supporting program execution, memory operations, disk management, audio playback, and device configuration through natural language commands.

SAP BusinessObjects BI MCP Server by CData

This project builds a read-only MCP server. For full read, write, update, delete, and action capabilities and a simplified setup, check out our free CData MCP Server for SAP BusinessObjects BI (beta): https://www.cdata.com/download/download.aspx?sku=GJZK-V&type=beta