Discover Awesome MCP Servers

ibmi-mcp

Give your AI Agent terminal access to your IBM i system via TN5250. ibmi-mcp is an MCP server that lets AI Agents like Claude interact with IBM i the same way a human would through a 5250 green-screen terminal.

DMAP-AI MCP Server

MCP server for DMAP-AI drought monitoring and SPI drought analysis using NASA POWER and ERA5-Land/CDS data.

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.

SAP Ariba MCP Server

Exposes 48 SAP Ariba APIs as Claude-compatible tools for managing procurement, sourcing, supplier management, and supply chain data. It enables AI agents to interact with contracts, catalogs, and business network transactions through natural language.

mcp-ip2whois

A Model Context Protocol (MCP) server that provides comprehensive WHOIS lookup capabilities using the IP2WHOIS API. This server allows AI agents to query domain registration details, including expiry dates, registrar information, and registrant data.

Coralogix MCP Server

A command-line tool for monitoring and analyzing Coralogix logs using the Model Control Protocol, providing tools to query and summarize log data.

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.

OpenCode MCP Tool

Enables AI assistants to interact with multiple AI models through the OpenCode CLI with a unified interface. Supports plan mode for structured analysis, flexible model selection, and natural language queries with file references.

synergy-age-mcp

MCP server providing structured access to the SynergyAge database of synergistic genetic interventions affecting lifespan, enabling AI assistants to query longevity research data via SQL.

mcp-duckvault

Provides a RAG system for your Obsidian Vault using DuckDB and vector search, enabling semantic search and note retrieval through AI agents.

boo-x402-mcp

Enables AI agents to access crypto/web3 data across 5 chains with pay-per-call billing in USDC via x402, no API key required, and built-in spend caps.

freqtrade-mcp

A read-only MCP server that provides LLMs with introspection data and documentation for the Freqtrade codebase. It enables AI tools to access class signatures, method details, and configuration schemas to assist in writing more reliable trading strategies.

AusLaw MCP

Enables users to search and retrieve Australian legislation and case law with full-text content extraction. Provides structured results with citation metadata and OCR support for archival PDFs.

Slack MCP Server

A Model Context Protocol server that enables LLMs to interact with Slack workspaces through OAuth 2.0 authentication. It provides tools for listing channels and posting messages while supporting secure token persistence and dynamic client registration.

Customs Big Data MCP Server

Provides comprehensive import/export trade data queries including export trends, product category statistics, order geographic distribution, and overseas certification information to help users understand enterprises' international trade situations.

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.

Production MCP Template

A production-grade, extensible Python template for building Model Context Protocol servers with support for Streamable HTTP and stdio transports. It provides a structured framework for implementing tools, resources, and prompts with built-in authentication, observability, and background task management.

Terminal MCP Server

Enables interactive terminal sessions within Claude Code and Desktop, allowing users and AI to execute commands and manage multiple tabs.

scout-mcp

Search 21 sources in one call — GitHub, npm, PyPI, arXiv, HN, X, Reddit, and more. No API keys to juggle, structured JSON back.

Upstox MCP Server

A lightweight, plugin-based MCP server for trading and fund analysis using Upstox APIs.

local-fusion MCP server

Exposes a multi-model council (panel-judge-synthesizer) and a build/check loop as MCP tools, enabling Claude Code or any MCP client to perform structured multi-model analysis and synthesis locally.

MCP LangChain Weather Agent

A weather MCP server that geocodes city names and fetches live weather from Open-Meteo, enabling a LangGraph agent to answer weather queries.

nannylane-mcp

Unofficial Bun-based MCP server and TypeScript SDK for authenticated Nanny Lane dashboard data, enabling reading dashboard data, searching public nanny listings, inspecting messages, and preparing messages.

slsk-mcp

An MCP server that enables AI assistants to log into Soulseek, search the network, and download files through simple tool calls.

MCP-BAMM

A Model Context Protocol server that enables interaction with Borrow Automated Market Maker (BAMM) contracts on the Fraxtal blockchain, allowing users to manage positions, borrow against LP tokens, and perform other BAMM-related operations.

mcp-memory

Smart memory for AI agents. Solves the Karpathy problem: memories decay, topics are frequency-weighted, one-time questions don't become obsessions. 7 tools. Zero deps.