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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.

Universal AI Memory MCP Server

Provides a local-first secure memory store with encrypted payloads, entity extraction, and vector persistence, exposing read, write, and delete tools with granular capability controls.

business-central-mcp

Gives AI assistants direct access to Microsoft Dynamics 365 Business Central via the native WebSocket protocol, replacing OData, APIs, and browser automation. Enables page navigation, data reading/writing, actions, searches, and report execution.

mcp-random

MCP server providing true randomness capabilities to Claude, enabling cryptographically secure random number generation for games, decision-making, sampling, simulations, and any operation requiring genuine randomness.

hyper-video-service

MCP server for programmatic video generation. Send a prompt, get an MP4.

CVM: Processos Administrativos Sancionadores

Enables read-only queries to official CVM (Brazilian Securities Commission) administrative sanctioning procedures via a paid, hosted MCP server. Works with any MCP-over-HTTP client like Claude, Cursor, and VS Code.

Personal DB MCP Server

Provides structured personal data (skills, experiences, values) as context to AI services, enabling personalized outputs across different AI applications.

weather-forecast-mcp

Enables querying South Korean meteorological observation data and short-term forecasts by region name or grid coordinates via the MCP protocol.

Math Solver AI MCP

Math Solver AI - MCP server providing AI-powered tools and automation by MEOK AI Labs

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.

Attio MCP Server

Provides tools to interact with the Attio API, enabling management of resources in an Attio workspace.

VIYAN MCP

Enables autonomous satellite agents to communicate and coordinate for orbital operations such as collision avoidance, maneuver planning, and mission execution.

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.

jira-mcp

A Model Context Protocol (MCP) server that provides tools for interacting with Jira. Enables Cursor and other MCP clients to fetch tickets, manage linked tickets, and update ticket status.

Datum

Enables natural-language querying of SQLite databases through a governed semantic layer, with citations and typed abstention for PII or uncertified data.

Eversince MCP Server

A creative agent that plans and executes across image, video, and audio. Uses 30+ tools, orchestrates 20+ AI models, and does agentic timeline editing.

OrchestrateKit MCP

Enables Cursor and Claude Desktop to design production-ready AI workflows by exposing a structured registry of components, edges, stacks, routes, and playbooks, with capabilities for goal matching, route composition, and confidence scoring.

python-base-mcp-server

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

Afro.tools MCP Server

Provides AI agents with structured, verified specs for African APIs like Wave and Paycard, enabling automatic integration code generation without manual documentation parsing.

Baidu Netdisk Knowledge MCP

Connects Baidu Netdisk to MCP-compatible AI clients, enabling AI to safely read selected files and generate summaries, key points, to-dos, tags, and organization suggestions.

@clikta/mcp-server

Enables Claude to drive a real browser and automatically turn interactions into Clikta interactive demos, step-by-step guides, and narrated videos.

@jambonz/mcp-schema-server

This server exposes jambonz verb schemas and developer documentation as MCP tools, enabling AI agents to query verb definitions, component types, callback payloads, and the full developer guide without needing local access to the schema files.

Pocket Connector

🔗 Servidor del Protocolo de Contexto del Modelo (MCP) para recuperar artículos guardados de la API de Pocket y cargarlos en Claude.

tsheets-mcp

Exposes the full public TSheets REST API v1 as MCP tools, enabling time tracking, scheduling, and PTO management operations via natural language.

Agent-MQ

agent-mq is a message queue that enables AI coding agents to communicate with each other across sessions and machines. Agents can send messages, delegate tasks, and coordinate work — all through MCP tools. Supports Claude Code, Cursor, Codex, OpenClaw, and any MCP-compatible tool. UUID-based authentication with per-user data isolation. Self-hostable with Docker.

AppCan Helper MCP Server

Enables users to search and access AppCan mobile development platform documentation with intelligent fuzzy search, caching, and content retrieval. Provides comprehensive access to AppCan's API documentation, development guides, and tutorials through natural language queries.

mcp-stytch-consumer-todo-list

An MCP server that manages a TODO list with user authentication via Stytch, enabling AI agents to interact with a full-stack application.