Discover Awesome MCP Servers

javaDemo

javaDemo. Contribute to zf0497/mydemo development by creating an account on GitHub.

MCP Server for X/Twitter

Automate your X account using the real browser API - JoshMayerr/mcp-x

Minima

On-premises conversational RAG with configurable containers - dmayboroda/minima

NutJS Windows Control

Cross-platform MCP server for OS automation. Contribute to Cheffromspace/MCPControl development by creating an account on GitHub.

WebSearch

Las herramientas de búsqueda web son una serie de herramientas que le permiten a Claude acceder a internet a través del servidor MCP.

GitHub Support Assistant

Ayuda a los ingenieros de soporte a encontrar problemas similares en GitHub para acelerar la resolución de problemas mediante la búsqueda en repositorios y el cálculo de puntuaciones de similitud basadas en las descripciones de los problemas.

Cloudflare API MCP Server

Lightweight MCP server to give your Cursor Agent access to the Cloudflare API

MCP Server for eSignatures

Facilita la gestión de contratos y plantillas para firmas electrónicas, permitiendo a los usuarios crear, enviar, actualizar y gestionar contratos y plantillas con opciones personalizables a través de una interfaz fácil de usar.

Inoyu Apache Unomi MCP Server

Un servidor de Protocolo de Contexto de Modelo que permite a Claude mantener el contexto del usuario a través de la gestión de perfiles de Apache Unomi.

JSON MCP Server

Una implementación de servidor del Protocolo de Contexto de Modelo que permite a los LLM consultar y manipular datos JSON utilizando la sintaxis JSONPath con operaciones extendidas para filtrar, ordenar, transformar y agregar datos.

Zotero MCP Server

This server allows users to interact with their Zotero library through the Model Context Protocol, providing tools for searching items, retrieving metadata, and accessing full text using natural language queries.

Radarr and Sonarr MCP Server

Un servidor de Protocolo de Contexto de Modelo basado en Python que permite a asistentes de IA como Claude acceder y consultar tu colección de películas y programas de televisión a través de las APIs de Radarr y Sonarr.

Coding Standards MCP Server

Proporciona herramientas para acceder a guías de estilo de codificación y mejores prácticas para diversas tecnologías, incluyendo Java, Python y React.

Semantic Scholar MCP Server

API de Semantic Scholar, que proporciona acceso integral a datos de artículos académicos, información de autores y redes de citas.

GitHub MCP Server

Repository management, file operations, and GitHub API integration

MCP Docling Server

Un servidor que proporciona capacidades de procesamiento de documentos utilizando el Protocolo de Contexto de Modelo, permitiendo la conversión de documentos a Markdown, la extracción de tablas y el procesamiento de imágenes de documentos.

MCP Tavily

A Model Context Protocol server enabling advanced search and content extraction using the Tavily API, with rich customization and integration options.

datadog

Okay, here's how you can access monitor and cluster logs from Datadog, broken down into steps and considerations: **1. Accessing Monitor Logs (Events):** * **Datadog UI:** * **Monitors Page:** Navigate to the "Monitors" section in the Datadog UI (usually under "Monitors" in the left-hand navigation). * **Monitor Details:** Click on the specific monitor you're interested in. This will take you to the monitor's detail page. * **Events Timeline:** On the monitor's detail page, you'll typically see an "Events" timeline or a similar section. This displays a history of when the monitor triggered (alerted) and when it recovered. You can filter this timeline by time range. * **Event Details:** Click on a specific event in the timeline to see more details about why the monitor triggered. This often includes: * The metric(s) that caused the alert. * The values of those metrics at the time of the alert. * Links to related dashboards or logs. * The monitor's evaluation results. * **Datadog API:** * You can use the Datadog API to programmatically retrieve monitor events. The relevant API endpoint is often related to "Events" or "Alerts." You'll need to authenticate with your Datadog API key and application key. * Example (Conceptual): `GET /api/v1/events?start=1678886400&end=1678972800&sources=monitor` (This is a simplified example; consult the Datadog API documentation for the exact parameters and format.) **2. Accessing Cluster Logs (Infrastructure Logs):** * **Datadog UI:** * **Logs Explorer:** Go to the "Logs" section in the Datadog UI (usually under "Logs" in the left-hand navigation). This is the primary interface for exploring your logs. * **Search and Filter:** Use the search bar and filters to narrow down the logs you want to see. Common filters for cluster logs include: * **Hostname:** Filter by the hostname of the specific server or node in your cluster. * **Service:** Filter by the service name (e.g., "nginx," "mysql," "kubernetes"). * **Source:** Filter by the log source (e.g., "systemd," "docker"). * **Tags:** If you've tagged your logs, you can filter by those tags (e.g., `env:production`, `cluster:my-cluster`). * **Keywords:** Search for specific keywords or error messages. * **Facets:** Use the facets on the left-hand side of the Logs Explorer to quickly filter by common attributes. * **Live Tail:** Use the "Live Tail" feature to see logs in real-time as they are ingested by Datadog. * **Datadog API:** * You can use the Datadog API to query and retrieve logs. The relevant API endpoint is usually related to "Logs." You'll need to authenticate with your Datadog API key and application key. * Example (Conceptual): `POST /api/v2/logs/events/search` (This is a simplified example; consult the Datadog API documentation for the exact parameters and format. You'll typically send a JSON payload with your search query and filters.) **3. Specific Cluster Types (e.g., Kubernetes):** * **Kubernetes Integration:** If you're using Kubernetes, make sure you have the Datadog Agent properly configured to collect logs from your Kubernetes cluster. This usually involves deploying the Datadog Agent as a DaemonSet. * **Kubernetes Logs in Datadog:** Once the integration is set up, you'll be able to filter your logs in the Datadog Logs Explorer by Kubernetes-specific attributes, such as: * `kube_namespace` * `kube_pod_name` * `kube_container_name` * `kube_deployment` * `kube_service` * **Kubernetes Events:** Datadog also collects Kubernetes events, which can be very helpful for troubleshooting. You can find these events in the Logs Explorer by filtering for the `source:kubernetes` and looking for log messages that represent Kubernetes events (e.g., pod creation, pod deletion, etc.). **4. Important Considerations:** * **Permissions:** Make sure you have the necessary permissions in Datadog to access the logs and monitors you need. Your Datadog administrator can grant you the appropriate roles. * **Retention:** Datadog has a log retention policy. Logs are typically stored for a certain period of time (e.g., 7 days, 30 days, etc.). Make sure the logs you need are still within the retention period. * **Log Volume:** If you have a high volume of logs, it can be challenging to find the specific logs you're looking for. Use filters and search queries effectively to narrow down your results. * **Log Format:** The format of your logs can impact how easily you can search and analyze them. Consider using a structured log format (e.g., JSON) to make it easier to parse and filter your logs. * **Tags:** Tagging your logs with relevant metadata (e.g., environment, application, component) can greatly improve your ability to search and filter them. * **Dashboards:** Create dashboards in Datadog to visualize your log data and monitor key metrics. You can add log widgets to your dashboards to display log counts, error rates, and other relevant information. * **Alerting:** Set up alerts in Datadog to notify you when specific log patterns or error messages occur. This can help you proactively identify and resolve issues. **Example Scenario (Kubernetes):** Let's say you want to troubleshoot an issue with a specific pod in your Kubernetes cluster. Here's how you might use Datadog: 1. **Identify the Pod:** Determine the name of the pod that's experiencing issues (e.g., `my-app-pod-123`). 2. **Go to Logs Explorer:** Navigate to the Logs Explorer in Datadog. 3. **Filter by Pod Name:** Enter `kube_pod_name:my-app-pod-123` in the search bar. 4. **Filter by Time Range:** Select the appropriate time range (e.g., the last hour, the last 24 hours). 5. **Look for Errors:** Scan the logs for error messages, warnings, or other suspicious patterns. You might also search for specific keywords related to the issue you're troubleshooting. 6. **Examine Related Logs:** If you find an error message, look for other logs that occurred around the same time. These logs might provide additional context or clues about the root cause of the issue. 7. **Check Kubernetes Events:** Filter for `source:kubernetes` and `kube_pod_name:my-app-pod-123` to see if there are any relevant Kubernetes events related to the pod (e.g., pod restarts, container crashes). **Spanish Translation of Key Terms:** * **Monitor:** Monitor * **Logs:** Registros * **Cluster:** Clúster * **Events:** Eventos * **Alert:** Alerta * **Dashboard:** Panel de control * **Hostname:** Nombre de host * **Service:** Servicio * **Source:** Fuente * **Tags:** Etiquetas * **Keywords:** Palabras clave * **Namespace:** Espacio de nombres * **Pod:** Pod * **Container:** Contenedor * **Deployment:** Despliegue * **Error:** Error * **Warning:** Advertencia * **Search:** Búsqueda * **Filter:** Filtro * **Retention:** Retención * **API Key:** Clave API * **Application Key:** Clave de aplicación By following these steps and using the appropriate filters and search queries, you should be able to effectively access and analyze your monitor and cluster logs in Datadog. Remember to consult the Datadog documentation for the most up-to-date information and specific instructions.

Penrose MCP Server

Facilita la creación de diagramas matemáticos utilizando lenguaje natural a través de los lenguajes de dominio específico de Penrose, permitiendo la definición de tipos matemáticos, relaciones y reglas de representación visual.

s3-tools

Un servidor MCP que proporciona herramientas para interactuar con buckets de AWS S3, permitiendo el acceso directo a las operaciones de S3 a través del Protocolo de Contexto del Modelo (MCP).

Elasticsearch Semantic Search MCP Server

Un servidor MCP de Python que permite la búsqueda semántica a través de las publicaciones del blog de Search Labs indexadas en Elasticsearch, lo que permite a Claude recuperar de forma inteligente información relevante del contenido del blog.

SolarWinds Logs MCP Server

Un servidor MCP para buscar y visualizar registros de SolarWinds Observability, que permite a los usuarios consultar datos de registro con opciones de filtrado y generar representaciones visuales de los eventos de registro a lo largo del tiempo.

DingTalk MCP Server V2

Un servidor de Protocolo de Control de Modelos para integrarse con DingTalk, que permite a los usuarios enviar mensajes, recuperar información de conversaciones/usuarios y consultar eventos del calendario a través de Claude.

MCP DuckDuckGo Search Plugin

Proporciona funcionalidad de búsqueda web a través de DuckDuckGo para clientes compatibles con Claude Code y MCP, con exploración avanzada de contenido, navegación a través de los resultados de búsqueda y análisis detallado de páginas web.

Webflow MCP Server

Permite a Claude interactuar con las APIs de Webflow para gestionar sitios, recuperar información y ejecutar tareas utilizando lenguaje natural.

Cloudflare MCP Server

Un servidor MCP que permite usar lenguaje natural para administrar recursos de Cloudflare (Workers, KV, R2, D1) a través de Claude Desktop, VSCode y otros clientes MCP.

DigitalFate MCP Server

Facilitates multi-client processing for high-performance operations within the DigitalFate framework, enabling advanced automation through task orchestration and agent integration.

Scraper.is MCP Server

Permite extraer datos de sitios web utilizando indicaciones en lenguaje natural, lo que permite a los usuarios especificar exactamente qué contenido desean en inglés sencillo y devuelve datos JSON estructurados.

ClickSend MCP Server

Este servidor permite que los modelos de IA envíen mensajes SMS e inicien llamadas de texto a voz de forma programática utilizando la API de ClickSend, con limitación de velocidad y validación de entrada integradas.