Discover Awesome MCP Servers

Getting Started with Remote MCP Servers using Azure Functions (.NET/C#)

Esta es una plantilla de inicio rápido para construir y desplegar fácilmente un servidor MCP remoto personalizado en la nube utilizando Azure Functions. Puedes clonar/restaurar/ejecutar en tu máquina local con depuración, y usar `azd up` para tenerlo en la nube en un par de minutos. El servidor MCP está asegurado por diseño utilizando

ynab-mcp

A Model Context Protocol (MCP) server for interacting with YNAB (You Need A Budget). Provides tools for accessing budget data through MCP-enabled clients like Claude Desktop.

Learn MCP Server

A Model Context Protocol (MCP) server designed for learning and experimentation. It provides a foundational setup for developers to build, run, and debug MCP server implementations using Node.js.

agentbay-mcp

Persistent memory, teams, and projects for AI agents. 76 MCP tools for storing, recalling, and sharing knowledge across sessions with 4-strategy hybrid search.

Code Executor MCP Server

Provides sandboxed code execution for AI agents with support for Python, JavaScript, and shell commands. Includes comprehensive safety features like destructive pattern blocking, timeout protection, and restricted file access for secure production use.

mcp_slack

fetch the latest channels messages chat

MCP NanoBanana

Enables AI image generation and editing using Google's Nano Banana model via the AceDataCloud API. It supports creating images from text prompts, virtual try-ons, and product placement directly within MCP-compatible clients.

Store Screenshot Generator MCP

Generates beautiful App Store and Play Store screenshots by inserting app images into iPhone/iPad mockup frames with customizable text overlays and gradient backgrounds. Supports multiple device types and batch generation with both free and pro subscription tiers.

Backlogr MCP Server

Enables AI assistants to create and manage development projects with structured backlogs, including tasks, requirements, and progress tracking. Provides a bridge between AI development assistants and project management workflows through standardized MCP tools.

MCP Declarative Server

A utility module for creating Model Context Protocol servers declaratively, allowing developers to easily define tools, prompts, and resources with a simplified syntax.

TMB Bus Arrival Times

Provides real-time bus arrival information for TMB (Transports Metropolitans de Barcelona) bus stops, showing when buses will arrive in minutes with line numbers, destinations, and directions.

Git Conflict MCP

Enables detection and resolution of Git merge conflicts in repositories through MCP, providing tools to identify conflicting files and assist with conflict resolution workflows.

Yahoo Finance MCP Server

Provides comprehensive access to Yahoo Finance data, including historical stock prices, financial statements, and analyst recommendations. It is designed for deployment on Cloudflare Workers and supports multiple transport methods to integrate market data into LLM workflows.

MCP Memory

An MCP server that gives AI assistants like Cursor, Claude and Windsurf the ability to remember user information across conversations using vector search technology.

lore-mcp

Architectural memory layer for AI coding. Automatically extracts decisions, detects security gaps, and analyzes git history from your codebase in one command.

SearXNG MCP Server

Enables AI agents to perform privacy-respecting web searches through SearXNG, with support for multiple search engines, categories, and advanced filtering options.

IBM DB2 MCP Server by CData

IBM DB2 MCP Server by CData

python-base-mcp-server

Una plantilla "cookiecutter" para iniciar rápidamente un servidor MCP basado en Python.

GitLab Pipeline MCP Server

Enables AI clients to manage GitLab pipelines through natural language commands. Supports triggering pipelines, checking status, listing pipelines, viewing jobs, and canceling pipelines across multiple GitLab instances.

FiveM MCP Server

A TypeScript-based server that provides debugging and management capabilities for FiveM plugin development, allowing developers to control plugins, monitor server logs, and execute RCON commands.

GitLab MCP Server

Connects AI assistants to GitLab, enabling natural language queries for merge requests, code reviews, pipeline tests, job logs, and commit discussions directly from chat.

Greenhouse 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 Greenhouse (beta): https://www.cdata.com/download/download.aspx?sku=PGZK-V&type=beta

Browser-use-claude-mcp

Un servidor MCP de automatización de navegador para modelos de IA como Claude y Gemini 2.5, que permite capacidades de navegación web a través del lenguaje natural.

Google MCP

Esta es una colección de herramientas nativas de Google (por ejemplo, Gmail, Calendar) para el protocolo MCP, diseñadas para integrarse perfectamente con clientes de IA como Claude o Cursor.

Hello Widget Example

A minimal ChatGPT app demonstrating interactive greeting widgets with confetti animations and theme support, built as an MCP server example using Smithery CLI.

Studio MCP Hub

StudioMCPHub is a production MCP server exposing a complete creative AI pipeline and the Alexandria Aeternum art dataset as paid tool calls. Agents connect via Streamable HTTP and pay per call with x402 USDC micropayments on Base L2 — no API keys, no accounts, no sign-up.

Reddit Buddy MCP

Enables AI assistants to browse Reddit, search posts, analyze user activity, and fetch comments without requiring API keys. Features smart caching, clean data responses, and optional authentication for higher rate limits.

Emcee

I can't directly "generate an MCP server" in the way you might be thinking. An MCP (Management Component Provider) server isn't a standard, universally defined term in the context of OpenAPI. It sounds like you're looking for a way to create a server that can manage and interact with an API defined by an OpenAPI document. Here's a breakdown of what you likely want and how to achieve it, along with the translation to Spanish: **Understanding the Goal (Entendiendo el Objetivo)** You want to create a server that: 1. **Understands an OpenAPI definition:** It can parse and interpret an OpenAPI (formerly Swagger) document (e.g., `openapi.yaml` or `openapi.json`). 2. **Provides an interface to manage the API:** This could include things like: * **Testing endpoints:** Sending requests and validating responses. * **Monitoring API health:** Tracking uptime, response times, and error rates. * **Configuration:** Setting API keys, rate limits, or other parameters. * **Security:** Managing authentication and authorization. * **Documentation:** Serving the OpenAPI documentation in a user-friendly format. 3. **Potentially acts as a proxy:** It might sit in front of the actual API implementation, adding features like caching, request transformation, or security policies. **How to Achieve This (Cómo Lograr Esto)** You have several options, ranging from using existing tools to building a custom solution: **1. Using Existing API Management Platforms (Usando Plataformas de Gestión de APIs Existentes)** This is the *recommended* approach for most use cases. These platforms are designed to do exactly what you want. They typically have features for importing OpenAPI definitions, managing APIs, and providing analytics. * **Examples (Ejemplos):** * **Kong:** A popular open-source API gateway. It can be configured with an OpenAPI definition to manage routing, authentication, and more. * **Apigee (Google Cloud):** A comprehensive API management platform. * **Azure API Management:** Microsoft's API management service. * **AWS API Gateway:** Amazon's API management service. * **Mulesoft Anypoint Platform:** A platform for API management and integration. * **Tyke:** An open-source API gateway. * **How to use (Cómo usar):** 1. **Choose a platform (Elige una plataforma).** 2. **Import your OpenAPI definition (Importa tu definición OpenAPI).** The platform will typically have a way to upload or link to your `openapi.yaml` or `openapi.json` file. 3. **Configure the platform (Configura la plataforma).** Set up routing rules, authentication, rate limits, and other settings based on your needs. 4. **Deploy the platform (Despliega la plataforma).** This usually involves deploying the platform to a server or cloud environment. **2. Using OpenAPI-Based Code Generation Tools (Usando Herramientas de Generación de Código Basadas en OpenAPI)** These tools can generate server stubs (basic code skeletons) from your OpenAPI definition. You then need to fill in the implementation logic. * **Examples (Ejemplos):** * **OpenAPI Generator:** A very popular and versatile tool that supports many languages and frameworks. * **Swagger Codegen (deprecated, use OpenAPI Generator):** The original code generation tool, now superseded by OpenAPI Generator. * **How to use (Cómo usar):** 1. **Install the tool (Instala la herramienta).** Follow the installation instructions for the chosen tool. 2. **Generate the server code (Genera el código del servidor).** Use the tool's command-line interface to generate code for your desired language and framework. For example, with OpenAPI Generator: ```bash openapi-generator generate -i openapi.yaml -g spring -o server-output ``` This command generates a Spring Boot server project based on `openapi.yaml` and places the output in the `server-output` directory. Replace `spring` with your desired generator (e.g., `nodejs-server`, `python-flask`). 3. **Implement the API logic (Implementa la lógica de la API).** Fill in the missing code in the generated server stubs to handle the actual API requests. 4. **Build and deploy the server (Construye y despliega el servidor).** Build the generated project and deploy it to a server environment. **3. Building a Custom Solution (Construyendo una Solución Personalizada)** This is the most complex option, but it gives you the most control. You'll need to write code to parse the OpenAPI definition, handle requests, and implement the management features you need. * **Steps (Pasos):** 1. **Choose a language and framework (Elige un lenguaje y un framework).** Popular choices include Python (Flask, Django), Node.js (Express), Java (Spring Boot), and Go. 2. **Use an OpenAPI parser library (Usa una biblioteca de análisis OpenAPI).** Libraries like `swagger-parser` (Java), `PyYAML` (Python), or `openapi3-ts` (TypeScript) can help you parse the OpenAPI document. 3. **Implement request handling (Implementa el manejo de solicitudes).** Write code to route incoming requests to the appropriate handlers based on the OpenAPI definition. 4. **Implement management features (Implementa las características de gestión).** Add code to handle testing, monitoring, configuration, and security. 5. **Build and deploy the server (Construye y despliega el servidor).** **Example (Ejemplo - Conceptual Python with Flask):** ```python # Conceptual - Requires significant implementation from flask import Flask, request, jsonify import yaml app = Flask(__name__) # Load OpenAPI definition with open("openapi.yaml", "r") as f: openapi_spec = yaml.safe_load(f) # Basic routing (very simplified) @app.route("/<path:path>", methods=['GET', 'POST', 'PUT', 'DELETE']) def handle_request(path): # TODO: Parse the OpenAPI spec to validate the request # TODO: Implement the actual API logic based on the path and method # TODO: Return a response return jsonify({"message": f"Request received for path: {path}"}) if __name__ == "__main__": app.run(debug=True) ``` **Translation to Spanish (Traducción al Español)** **Generar un servidor MCP para cualquier endpoint documentado con OpenAPI.** Como mencioné antes, "servidor MCP" no es un término estándar en el contexto de OpenAPI. Parece que buscas una forma de crear un servidor que pueda gestionar e interactuar con una API definida por un documento OpenAPI. Aquí tienes un desglose de lo que probablemente quieres y cómo lograrlo: **Entendiendo el Objetivo** Quieres crear un servidor que: 1. **Entienda una definición OpenAPI:** Que pueda analizar e interpretar un documento OpenAPI (anteriormente Swagger) (por ejemplo, `openapi.yaml` o `openapi.json`). 2. **Proporcione una interfaz para gestionar la API:** Esto podría incluir cosas como: * **Probar endpoints:** Enviar solicitudes y validar respuestas. * **Monitorizar la salud de la API:** Rastrear el tiempo de actividad, los tiempos de respuesta y las tasas de error. * **Configuración:** Establecer claves de API, límites de velocidad u otros parámetros. * **Seguridad:** Gestionar la autenticación y la autorización. * **Documentación:** Servir la documentación OpenAPI en un formato fácil de usar. 3. **Potencialmente actúe como un proxy:** Podría situarse frente a la implementación real de la API, añadiendo características como el almacenamiento en caché, la transformación de solicitudes o las políticas de seguridad. **Cómo Lograr Esto** Tienes varias opciones, que van desde el uso de herramientas existentes hasta la construcción de una solución personalizada: **1. Usando Plataformas de Gestión de APIs Existentes** Este es el enfoque *recomendado* para la mayoría de los casos de uso. Estas plataformas están diseñadas para hacer exactamente lo que quieres. Normalmente tienen características para importar definiciones OpenAPI, gestionar APIs y proporcionar análisis. * **Ejemplos:** * **Kong:** Una pasarela de API de código abierto popular. Se puede configurar con una definición OpenAPI para gestionar el enrutamiento, la autenticación y más. * **Apigee (Google Cloud):** Una plataforma integral de gestión de APIs. * **Azure API Management:** El servicio de gestión de APIs de Microsoft. * **AWS API Gateway:** El servicio de gestión de APIs de Amazon. * **Mulesoft Anypoint Platform:** Una plataforma para la gestión e integración de APIs. * **Tyke:** Una pasarela de API de código abierto. * **Cómo usar:** 1. **Elige una plataforma.** 2. **Importa tu definición OpenAPI.** La plataforma normalmente tendrá una forma de cargar o enlazar a tu archivo `openapi.yaml` o `openapi.json`. 3. **Configura la plataforma.** Configura las reglas de enrutamiento, la autenticación, los límites de velocidad y otros ajustes según tus necesidades. 4. **Despliega la plataforma.** Esto normalmente implica desplegar la plataforma en un servidor o entorno de nube. **2. Usando Herramientas de Generación de Código Basadas en OpenAPI** Estas herramientas pueden generar stubs de servidor (esqueletos de código básicos) a partir de tu definición OpenAPI. Luego necesitas rellenar la lógica de implementación. * **Ejemplos:** * **OpenAPI Generator:** Una herramienta muy popular y versátil que soporta muchos lenguajes y frameworks. * **Swagger Codegen (obsoleto, usa OpenAPI Generator):** La herramienta original de generación de código, ahora reemplazada por OpenAPI Generator. * **Cómo usar:** 1. **Instala la herramienta.** Sigue las instrucciones de instalación de la herramienta elegida. 2. **Genera el código del servidor.** Usa la interfaz de línea de comandos de la herramienta para generar código para tu lenguaje y framework deseados. Por ejemplo, con OpenAPI Generator: ```bash openapi-generator generate -i openapi.yaml -g spring -o server-output ``` Este comando genera un proyecto de servidor Spring Boot basado en `openapi.yaml` y coloca la salida en el directorio `server-output`. Reemplaza `spring` con tu generador deseado (por ejemplo, `nodejs-server`, `python-flask`). 3. **Implementa la lógica de la API.** Rellena el código que falta en los stubs de servidor generados para manejar las solicitudes de la API reales. 4. **Construye y despliega el servidor.** Construye el proyecto generado y despliégalo en un entorno de servidor. **3. Construyendo una Solución Personalizada** Esta es la opción más compleja, pero te da el mayor control. Necesitarás escribir código para analizar la definición OpenAPI, manejar las solicitudes e implementar las características de gestión que necesitas. * **Pasos:** 1. **Elige un lenguaje y un framework.** Las opciones populares incluyen Python (Flask, Django), Node.js (Express), Java (Spring Boot) y Go. 2. **Usa una biblioteca de análisis OpenAPI.** Bibliotecas como `swagger-parser` (Java), `PyYAML` (Python) o `openapi3-ts` (TypeScript) pueden ayudarte a analizar el documento OpenAPI. 3. **Implementa el manejo de solicitudes.** Escribe código para enrutar las solicitudes entrantes a los manejadores apropiados basándose en la definición OpenAPI. 4. **Implementa las características de gestión.** Añade código para manejar las pruebas, la monitorización, la configuración y la seguridad. 5. **Construye y despliega el servidor.** **Important Considerations (Consideraciones Importantes):** * **Security:** Always prioritize security when building or configuring an API server. Use HTTPS, validate input, and implement proper authentication and authorization. * **Error Handling:** Implement robust error handling to provide informative error messages to clients. * **Scalability:** Consider the scalability of your solution, especially if you expect a high volume of traffic. * **Monitoring:** Set up monitoring to track the performance and health of your API. By following these steps and choosing the right tools, you can create a server that effectively manages and interacts with your OpenAPI-documented API. Remember to choose the approach that best suits your needs and technical expertise.

Shiprocket MCP Integration

Enables interaction with Shiprocket shipping services to check courier rates and delivery times, create and manage orders, ship packages, track shipments, and schedule pickups through natural language commands.

Limitless AI MCP Server

Connects AI assistants to your Limitless AI lifelog data, enabling them to search, retrieve, and analyze your recorded conversations and daily activities from your Limitless pendant.