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Limitless MCP Integration

A Model Context Protocol server, client and interactive mode for Limitless API

postgres-mcp MCP server

Postgres Pro es un servidor de Protocolo de Contexto de Modelo (MCP) de código abierto creado para brindarte soporte a ti y a tus agentes de IA durante todo el proceso de desarrollo, desde la codificación inicial, pasando por las pruebas y la implementación, hasta el ajuste y el mantenimiento de la producción.

What is Model Context Protocol (MCP)?

Un servidor de Protocolo de Contexto de Modelo (MCP) ligero que permite a tu LLM validar direcciones de correo electrónico. Esta herramienta verifica el formato del correo electrónico, la validez del dominio y la capacidad de entrega utilizando la API de Validación de Correo Electrónico de AbstractAPI. Perfecto para integrar la validación de correo electrónico en aplicaciones de IA como Claude Desktop.

Weather MCP Server

Un servidor de Protocolo de Contexto de Modelo que proporciona información meteorológica.

Cortellis MCP Server

An MCP server enabling AI assistants to search and analyze pharmaceutical data through Cortellis. Features comprehensive drug search, ontology exploration, and real-time clinical trial data access.

Workers MCP Server

Talk to a Cloudflare Worker from Claude Desktop!

Waldzell MCP Servers

Monorepositorio de servidores MCP de Waldzell AI. ¡Se usa en Claude Desktop, Cline, Roo Code y más!

Goose FM

Okay, here's a breakdown of an MVP (Minimum Viable Product) for an MCP (Minecraft Protocol) server that allows AI assistants to "tune into" FM radio stations within Minecraft. This focuses on core functionality and avoids unnecessary complexity for the initial release. **Core Concept:** The AI assistant (e.g., a Python script using a library like `minecraft-protocol`) connects to the Minecraft server. It sends commands to interact with a virtual "radio" block. The server then streams audio from a real-world FM radio station to the AI assistant. **MVP Features:** 1. **Basic MCP Server:** * **Implementation:** Use a lightweight MCP server library (e.g., `node-minecraft-protocol` for Node.js, or `mcproto` for Python). Focus on handling basic connection and command parsing. * **Functionality:** * Accept connections from a single AI assistant client. * Authenticate the client (simple password or token-based authentication). * Handle basic chat messages (for debugging and status). 2. **Virtual Radio Block:** * **Representation:** A single, designated block in the Minecraft world (e.g., a specific type of block at a fixed coordinate). * **Interaction:** * The AI assistant sends a command to "interact" with the radio block (e.g., `/radio on`, `/radio off`, `/radio station <frequency>`). The server parses these commands. * The server sends feedback to the AI assistant (e.g., "Radio turned on", "Tuning to 98.7 FM", "Radio turned off"). This can be done via chat messages or custom packets. 3. **FM Radio Streaming:** * **Radio Source:** Use a reliable online FM radio streaming service or a local FM receiver connected to the server. Consider using a library like `vlc` or `ffmpeg` to capture the audio stream. * **Audio Encoding:** Encode the audio stream into a format suitable for transmission over the network (e.g., MP3, Opus). Keep the bitrate low to minimize bandwidth usage. * **Streaming to AI Assistant:** * Establish a separate TCP connection (or use WebSockets) between the server and the AI assistant for audio streaming. * Send audio data in small chunks to the AI assistant. * Implement basic error handling (e.g., reconnect if the stream is interrupted). 4. **AI Assistant Client (Example in Python):** ```python import minecraft_protocol import socket import threading import time SERVER_ADDRESS = ("localhost", 25565) # Replace with your server's address USERNAME = "AI_Assistant" PASSWORD = "password" # Replace with your password RADIO_STREAM_PORT = 12345 # Port for audio stream def receive_audio(sock): try: while True: data = sock.recv(1024) # Adjust buffer size as needed if not data: break # Process audio data (e.g., play it using a library like PyAudio) print(f"Received audio data: {len(data)} bytes") # Replace with actual audio playback except Exception as e: print(f"Error receiving audio: {e}") finally: sock.close() def main(): try: client = minecraft_protocol.Client(SERVER_ADDRESS[0], SERVER_ADDRESS[1], USERNAME) client.login(USERNAME, PASSWORD) print("Connected to Minecraft server.") # Connect to audio stream audio_socket = socket.socket(socket.AF_INET, socket.SOCK_STREAM) audio_socket.connect((SERVER_ADDRESS[0], RADIO_STREAM_PORT)) print("Connected to audio stream.") audio_thread = threading.Thread(target=receive_audio, args=(audio_socket,)) audio_thread.daemon = True audio_thread.start() # Send commands to the server client.chat("/radio on") time.sleep(2) client.chat("/radio station 98.7") time.sleep(10) # Listen for a while client.chat("/radio off") client.close() print("Disconnected from Minecraft server.") except Exception as e: print(f"Error: {e}") if __name__ == "__main__": main() ``` **Technical Considerations:** * **Audio Latency:** Streaming audio over a network will introduce latency. Minimize this by using a low bitrate and efficient encoding. * **Bandwidth:** Consider the bandwidth requirements of streaming audio, especially if multiple AI assistants are connected. * **Error Handling:** Implement robust error handling to deal with network interruptions, invalid commands, and other potential issues. * **Security:** For the MVP, simple authentication is sufficient. For a production system, use more secure authentication methods. * **Scalability:** The MVP is designed for a single AI assistant. Consider scalability issues if you plan to support multiple clients. **Development Steps:** 1. **Set up the MCP server:** Choose a library and implement the basic server functionality (connection handling, authentication, chat). 2. **Implement the virtual radio block:** Define the block and handle the `/radio` commands. 3. **Implement the FM radio streaming:** Capture audio from a source, encode it, and stream it to the AI assistant. 4. **Develop the AI assistant client:** Connect to the server, send commands, and receive and play the audio stream. 5. **Test and debug:** Thoroughly test the system to identify and fix any issues. **Why this is an MVP:** * **Focus on core functionality:** It only implements the essential features needed to demonstrate the concept. * **Limited scope:** It supports a single AI assistant and a single radio block. * **Simplified implementation:** It uses simple authentication and error handling. * **Iterative development:** This MVP can be used as a foundation for adding more features and improving the system over time. **Possible Future Enhancements:** * **Multiple radio stations:** Allow the AI assistant to select from a list of available stations. * **Volume control:** Implement volume control for the radio. * **User interface:** Create a more user-friendly interface for the AI assistant. * **Multiple AI assistants:** Support multiple AI assistants connecting to the server. * **Integration with other Minecraft features:** Integrate the radio with other Minecraft features, such as redstone circuits. * **Spatial Audio:** Make the audio louder the closer you are to the radio block. This MVP provides a solid starting point for building a more complex and feature-rich system. Remember to prioritize simplicity and focus on delivering a working product as quickly as possible. Good luck!

My Slack MCP Server Extension

Una extensión para el servidor MCP de Slack.

mcp-oceanbase

Here are a few options for translating "MCP Server for OceanBase database and its tools," depending on the specific context and desired nuance: **Option 1 (Most straightforward):** * **Servidor MCP para la base de datos OceanBase y sus herramientas** * This is a direct translation and is generally suitable. **Option 2 (More descriptive, emphasizing the purpose):** * **Servidor MCP para la gestión de la base de datos OceanBase y sus herramientas** * This option uses "gestión" (management) to clarify the server's role. **Option 3 (If "MCP" is an acronym that's not commonly used in Spanish):** * **Servidor MCP (Servidor de Control de Mantenimiento, si aplica) para la base de datos OceanBase y sus herramientas** * This option provides a possible expansion of the acronym "MCP" in parentheses, but only if you know what it stands for and if that expansion is relevant in Spanish. If "MCP" is widely understood as "MCP" even in Spanish-speaking contexts, then stick with Option 1. **Key Considerations:** * **"OceanBase":** The name "OceanBase" should remain as is, as it's a proper noun. * **"Tools":** "Herramientas" is the standard translation for "tools." * **Context:** The best option depends on the audience and the specific purpose of the translation. If you're writing for a technical audience familiar with the term "MCP," the simplest translation (Option 1) is likely sufficient. If you need to be more explicit about the server's function, Option 2 might be better. Therefore, I recommend **Servidor MCP para la base de datos OceanBase y sus herramientas** unless you have a specific reason to use one of the other options.

mcp-server-proxy

Converts MCP protocol's SSE transport layer to a standard HTTP request/response.

Podman MCP Server

Model Context Protocol (MCP) server for container runtimes (Podman and Docker)

Coinmarket MCP server

Mirror of

Quarkus Model Context Protocol (MCP) Server

Mirror of

Dify as MCP Server

Expone las aplicaciones de Dify (tanto Chatflow como Workflow) como servidores MCP (Protocolo de Contexto de Modelo), permitiendo que Claude y otros clientes MCP interactúen directamente con las aplicaciones de Dify a través de un protocolo estandarizado.

MCP Dockmaster

MCP Dockmaster allows you to easily install and manage MCP servers. Available for Mac, Windows and Linux as a Desktop App, CLI and a library.

Claude Desktop Commander MCP

Permite a Claude ejecutar comandos de terminal en tu computadora y realizar operaciones en el sistema de archivos, incluyendo la edición quirúrgica de código con reemplazos basados en diff.

imagegen-go MCP 服务器

MCP server which will trigger OpenAI to generate image

Firecrawl MCP Server

Espejo de

DevRev MCP server

Mirror of

FastMCP 🚀

The fast, Pythonic way to build Model Context Protocol servers 🚀

Modern Control Protocol (MCP) Server

A modern, scalable MCP server implementation with support for multiple AI providers, advanced monitoring, and robust conversation management.

mcp-clj

A MCP server written in clojure

MCP Server

Una implementación basada en FastAPI del Protocolo de Contexto del Modelo que permite una interacción estandarizada entre los modelos de IA y los entornos de desarrollo, facilitando a los desarrolladores la integración y gestión de tareas de IA.

Govee MCP Server

Mirror of