Discover Awesome MCP Servers

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.

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.

SWLC MCP Server

A lottery information query service for the Shanghai region that provides winning number lookups and analysis functions for various lottery games including Double Color Ball, 3D Lottery, and Seven Happiness Lottery.

AEM Block Collection MCP Server

Enables access to AEM block metadata by reading structured information from blocks.json files. Provides a simple tool to list available blocks with their descriptions, file paths, and counts.

Tri-Tender Pricing MCP

An MCP server designed to automate tender and RFQ pricing by extracting requirements from documents and building structured pricing models. It enables users to calculate final costs, compare market rates, and generate styled HTML pricing reports for PDF export.

Random.org MCP Server

A Model Context Protocol server that provides access to api.random.org for generating true random numbers, strings, UUIDs, and more.

Istek MCP Server

Enables AI assistants to interact with Istek API Client for managing workspaces, collections, environments, variables, and request history. Allows natural language control of API development workflows including creating collections, adding requests, and managing environment configurations.

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.

CLI MCP Server

A simplified MCP server for terminal command execution

Trapper Keeper MCP

An MCP server that automatically manages and organizes project documentation using the document reference pattern, keeping CLAUDE.md files clean and under 500 lines while maintaining full context for AI assistants.

WHOOP MCP Server

Connects WHOOP fitness data to Claude Desktop, enabling natural language queries about workouts, recovery, sleep patterns, and physiological cycles with secure OAuth authentication and local data storage.

NDB MCP Server

Enables Claude and other MCP-compatible AI assistants to manage Nutanix Database Service (NDB) environments through natural language, supporting database operations like provisioning, cloning, backups, and monitoring with customizable instructions and behavior controls.

Hubble MCP Server

A Python-based Model Context Protocol server that integrates with Claude Desktop, allowing users to connect to Hubble API services by configuring the server with their Hubble API key.

arXiv MCP Server

Enables interaction with arXiv.org to search scholarly articles, retrieve metadata, download PDFs, and load article content directly into LLM context for analysis.

Jina AI Remote MCP Server

Provides access to Jina AI's suite of tools including web search, URL reading, image search, embeddings, and reranking capabilities. Enables users to extract web content as markdown, search academic papers, capture screenshots, and perform semantic operations through natural language.

Mendix Context Bridge

Enables AI agents to read and understand local Mendix project structure and logic by connecting directly to the .mpr file via MCP. Allows querying microflows, entities, attributes, and modules in read-only mode without requiring cloud access.

FastMCP ThreatIntel

Enables AI-powered threat intelligence analysis of IPs, domains, URLs, and file hashes across multiple threat intelligence platforms (VirusTotal, AlienVault OTX, AbuseIPDB, IPinfo) with APT attribution and interactive reporting through natural language queries.

python-base-mcp-server

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

MCP Image Recognition Server

Enables image analysis and recognition through multiple LLM vision models (Gemini, GPT-4o, Qwen-VL, Doubao) by accepting image URLs or Base64 data and returning text descriptions or answers to questions about the images.

Azure Log Analytics MCP Server

Enables querying and managing Azure Log Analytics workspaces using KQL (Kusto Query Language). Supports executing queries, managing saved queries, and exploring workspace tables and schemas with Service Principal authentication.

AI Book Agent MCP Server

Provides AI assistants with intelligent access to ML textbook content for creating accurate, source-grounded documentation using local models for privacy and cost efficiency.

Feishu MCP Server

A remote Model Context Protocol server for Feishu (Lark) that supports OAuth authentication and deployment on Cloudflare Workers. It allows AI clients to interact with Feishu documents, perform content searches, and manage document blocks with a zero-configuration experience.

Apple MCP Server

Enables interaction with Apple apps like Messages, Notes, and Contacts through the MCP protocol to send messages, search, and open app content using natural language.

Amap MCP Server

Provides comprehensive geographic information services and route planning for AI agents via the Amap (Gaode Maps) API. It supports geocoding, multi-modal navigation, POI searches, and administrative region queries.

Netmind Web3 MCP Server

Provides a comprehensive suite of Web3 tools for querying token addresses, news summaries, and real-time market data via CoinGecko. It also facilitates DeFi operations including token price tracking, pool information, and swap quotes through Sugar DeFi integration.

TradingView MCP Server

Enables trading analysis across Forex, Stocks, and Crypto with 25+ technical indicators, real-time market data, and Pine Script v6 development tools including syntax validation, autocomplete, and version conversion.

Document Organizer MCP Server

Enables systematic document organization with PDF-to-Markdown conversion, intelligent categorization, and automated workflow management. Supports project documentation standards and provides complete end-to-end document processing pipelines.

MCP Desktop Tools

An MCP server that provides Claude with comprehensive desktop automation capabilities including browser control, window management, and native mouse/keyboard input on Windows. It enables users to capture screenshots, launch applications, and interact with the system clipboard through natural language.