[{"_1":2,"_705":-5,"_706":-5},"loaderData",{"_3":4,"_22":23,"_24":25,"_495":496},"root",{"_5":6,"_7":8},"toasts",[],"visitor",{"_9":10,"_11":12},"viewportWidth",1280,"visitorSession",{"_13":14,"_16":17,"_18":-5,"_19":20,"_21":-5},"attributes",[15],"BOT","id",8817910,"membership","referenceId","0197cc96-976d-74e1-98b5-db64541084fe","userAccount","routes/_public/_layout",{},"routes/_public/mcp/servers/~namespace/~slug/_pages/_layout",{"_26":27,"_66":-5,"_67":28,"_29":68,"_414":415,"_494":301},"availableLocales",[28,40,46,52,59],{"_29":30,"_33":37,"_38":39},"mcpServer",{"_31":32,"_33":34,"_35":36},"description","The MCP server provides an interface to the Datadog API, enabling seamless management of incidents, monitoring, logs, dashboards, metrics, traces, and hosts. Its extensible design allows easy integration of additional Datadog APIs for future expansions.","name","mcp-server-datadog","readme","# Datadog MCP Server\n\n> **DISCLAIMER**: This is a community-maintained project and is not officially affiliated with, endorsed by, or supported by Datadog, Inc. This MCP server utilizes the Datadog API but is developed independently as part of the [Model Context Protocol](https://github.com/modelcontextprotocol/servers) ecosystem.\n\n![NPM Version](https://img.shields.io/npm/v/%40winor30%2Fmcp-server-datadog)![Build and Test](https://github.com/winor30/mcp-server-datadog/actions/workflows/ci.yml/badge.svg)[![codecov](https://codecov.io/gh/winor30/mcp-server-datadog/graph/badge.svg?token=BG4ZB74X92)](https://codecov.io/gh/winor30/mcp-server-datadog)[![smithery badge](https://smithery.ai/badge/@winor30/mcp-server-datadog)](https://smithery.ai/server/@winor30/mcp-server-datadog)\n\nMCP server for the Datadog API, enabling incident management and more.\n\n\n $\"mcp-server-datadog$ \n\n\n## Features\n\n- **Observability Tools**: Provides a mechanism to leverage key Datadog monitoring features, such as incidents, monitors, logs, dashboards, and metrics, through the MCP server.\n- **Extensible Design**: Designed to easily integrate with additional Datadog APIs, allowing for seamless future feature expansion.\n\n## Tools\n\n1. `list_incidents`\n\n - Retrieve a list of incidents from Datadog.\n - **Inputs**:\n - `filter` (optional string): Filter parameters for incidents (e.g., status, priority).\n - `pagination` (optional object): Pagination details like page size/offset.\n - **Returns**: Array of Datadog incidents and associated metadata.\n\n2. `get_incident`\n\n - Retrieve detailed information about a specific Datadog incident.\n - **Inputs**:\n - `incident_id` (string): Incident ID to fetch details for.\n - **Returns**: Detailed incident information (title, status, timestamps, etc.).\n\n3. `get_monitors`\n\n - Fetch the status of Datadog monitors.\n - **Inputs**:\n - `groupStates` (optional array): States to filter (e.g., alert, warn, no data, ok).\n - `name` (optional string): Filter by name.\n - `tags` (optional array): Filter by tags.\n - **Returns**: Monitors data and a summary of their statuses.\n\n4. `get_logs`\n\n - Search and retrieve logs from Datadog.\n - **Inputs**:\n - `query` (string): Datadog logs query string.\n - `from` (number): Start time in epoch seconds.\n - `to` (number): End time in epoch seconds.\n - `limit` (optional number): Maximum number of logs to return (defaults to 100).\n - **Returns**: Array of matching logs.\n\n5. `list_dashboards`\n\n - Get a list of dashboards from Datadog.\n - **Inputs**:\n - `name` (optional string): Filter dashboards by name.\n - `tags` (optional array): Filter dashboards by tags.\n - **Returns**: Array of dashboards with URL references.\n\n6. `get_dashboard`\n\n - Retrieve a specific dashboard from Datadog.\n - **Inputs**:\n - `dashboard_id` (string): ID of the dashboard to fetch.\n - **Returns**: Dashboard details including title, widgets, etc.\n\n7. `query_metrics`\n\n - Retrieve metrics data from Datadog.\n - **Inputs**:\n - `query` (string): Metrics query string.\n - `from` (number): Start time in epoch seconds.\n - `to` (number): End time in epoch seconds.\n - **Returns**: Metrics data for the queried timeframe.\n\n8. `list_traces`\n\n - Retrieve a list of APM traces from Datadog.\n - **Inputs**:\n - `query` (string): Datadog APM trace query string.\n - `from` (number): Start time in epoch seconds.\n - `to` (number): End time in epoch seconds.\n - `limit` (optional number): Maximum number of traces to return (defaults to 100).\n - `sort` (optional string): Sort order for traces (defaults to '-timestamp').\n - `service` (optional string): Filter by service name.\n - `operation` (optional string): Filter by operation name.\n - **Returns**: Array of matching traces from Datadog APM.\n\n9. `list_hosts`\n\n - Get list of hosts from Datadog.\n - **Inputs**:\n - `filter` (optional string): Filter string for search results.\n - `sort_field` (optional string): Field to sort hosts by.\n - `sort_dir` (optional string): Sort direction (asc/desc).\n - `start` (optional number): Starting offset for pagination.\n - `count` (optional number): Max number of hosts to return (max: 1000).\n - `from` (optional number): Search hosts from this UNIX timestamp.\n - `include_muted_hosts_data` (optional boolean): Include muted hosts status and expiry.\n - `include_hosts_metadata` (optional boolean): Include host metadata (version, platform, etc).\n - **Returns**: Array of hosts with details including name, ID, aliases, apps, mute status, and more.\n\n10. `get_active_hosts_count`\n\n - Get the total number of active hosts in Datadog.\n - **Inputs**:\n - `from` (optional number): Number of seconds from which you want to get total number of active hosts (defaults to 2h).\n - **Returns**: Count of total active and up hosts.\n\n11. `mute_host`\n\n - Mute a host in Datadog.\n - **Inputs**:\n - `hostname` (string): The name of the host to mute.\n - `message` (optional string): Message to associate with the muting of this host.\n - `end` (optional number): POSIX timestamp for when the mute should end.\n - `override` (optional boolean): If true and the host is already muted, replaces existing end time.\n - **Returns**: Success status and confirmation message.\n\n12. `unmute_host`\n\n - Unmute a host in Datadog.\n - **Inputs**:\n - `hostname` (string): The name of the host to unmute.\n - **Returns**: Success status and confirmation message.\n\n13. `list_downtimes`\n\n - List scheduled downtimes from Datadog.\n - **Inputs**:\n - `currentOnly` (optional boolean): Return only currently active downtimes when true.\n - `monitorId` (optional number): Filter by monitor ID.\n - **Returns**: Array of scheduled downtimes with details including scope, monitor information, and schedule.\n\n14. `schedule_downtime`\n\n - Schedule a downtime in Datadog.\n - **Inputs**:\n - `scope` (string): Scope to apply downtime to (e.g. 'host:my-host').\n - `start` (optional number): UNIX timestamp for the start of the downtime.\n - `end` (optional number): UNIX timestamp for the end of the downtime.\n - `message` (optional string): A message to include with the downtime.\n - `timezone` (optional string): The timezone for the downtime (e.g. 'UTC', 'America/New_York').\n - `monitorId` (optional number): The ID of the monitor to mute.\n - `monitorTags` (optional array): A list of monitor tags for filtering.\n - `recurrence` (optional object): Recurrence settings for the downtime.\n - `type` (string): Recurrence type ('days', 'weeks', 'months', 'years').\n - `period` (number): How often to repeat (must be >= 1).\n - `weekDays` (optional array): Days of the week for weekly recurrence.\n - `until` (optional number): UNIX timestamp for when the recurrence ends.\n - **Returns**: Scheduled downtime details including ID and active status.\n\n15. `cancel_downtime`\n\n - Cancel a scheduled downtime in Datadog.\n - **Inputs**:\n - `downtimeId` (number): The ID of the downtime to cancel.\n - **Returns**: Confirmation of downtime cancellation.\n\n16. `get_rum_applications`\n\n - Get all RUM applications in the organization.\n - **Inputs**: None.\n - **Returns**: List of RUM applications.\n\n17. `get_rum_events`\n\n - Search and retrieve RUM events from Datadog.\n - **Inputs**:\n - `query` (string): Datadog RUM query string.\n - `from` (number): Start time in epoch seconds.\n - `to` (number): End time in epoch seconds.\n - `limit` (optional number): Maximum number of events to return (default: 100).\n - **Returns**: Array of RUM events.\n\n18. `get_rum_grouped_event_count`\n\n - Search, group and count RUM events by a specified dimension.\n - **Inputs**:\n - `query` (optional string): Additional query filter for RUM search (default: \"\\*\").\n - `from` (number): Start time in epoch seconds.\n - `to` (number): End time in epoch seconds.\n - `groupBy` (optional string): Dimension to group results by (default: \"application.name\").\n - **Returns**: Grouped event counts.\n\n19. `get_rum_page_performance`\n\n - Get page (view) performance metrics from RUM data.\n - **Inputs**:\n - `query` (optional string): Additional query filter for RUM search (default: \"\\*\").\n - `from` (number): Start time in epoch seconds.\n - `to` (number): End time in epoch seconds.\n - `metricNames` (array of strings): Array of metric names to retrieve (e.g., 'view.load_time', 'view.first_contentful_paint').\n - **Returns**: Performance metrics including average, min, max, and count for each metric.\n\n20. `get_rum_page_waterfall`\n\n - Retrieve RUM page (view) waterfall data filtered by application name and session ID.\n - **Inputs**:\n - `applicationName` (string): Application name to filter events.\n - `sessionId` (string): Session ID to filter events.\n - **Returns**: Waterfall data for the specified application and session.\n\n## Setup\n\n### Datadog Credentials\n\nYou need valid Datadog API credentials to use this MCP server:\n\n- `DATADOG_API_KEY`: Your Datadog API key\n- `DATADOG_APP_KEY`: Your Datadog Application key\n- `DATADOG_SITE` (optional): The Datadog site (e.g. `datadoghq.eu`)\n\nExport them in your environment before running the server:\n\n```bash\nexport DATADOG_API_KEY=\"your_api_key\"\nexport DATADOG_APP_KEY=\"your_app_key\"\nexport DATADOG_SITE=\"your_datadog_site\"\n```\n\n## Installation\n\n### Installing via Smithery\n\nTo install Datadog MCP Server for Claude Desktop automatically via [Smithery](https://smithery.ai/server/@winor30/mcp-server-datadog):\n\n```bash\nnpx -y @smithery/cli install @winor30/mcp-server-datadog --client claude\n```\n\n### Manual Installation\n\n```bash\npnpm install\npnpm build\npnpm watch # for development with auto-rebuild\n```\n\n## Usage with Claude Desktop\n\nTo use this with Claude Desktop, add the following to your `claude_desktop_config.json`:\n\nOn MacOS: `~/Library/Application Support/Claude/claude_desktop_config.json` \nOn Windows: `%APPDATA%/Claude/claude_desktop_config.json`\n\n```json\n{\n \"mcpServers\": {\n \"github\": {\n \"command\": \"npx\",\n \"args\": [\"-y\", \"@modelcontextprotocol/server-github\"],\n \"env\": {\n \"GITHUB_PERSONAL_ACCESS_TOKEN\": \"\"\n }\n }\n }\n}\n```\n\n```json\n{\n \"mcpServers\": {\n \"datadog\": {\n \"command\": \"/path/to/mcp-server-datadog/build/index.js\",\n \"env\": {\n \"DATADOG_API_KEY\": \"\",\n \"DATADOG_APP_KEY\": \"\",\n \"DATADOG_SITE\": \"\" // Optional\n }\n }\n }\n}\n```\n\nOr specify via `npx`:\n\n```json\n{\n \"mcpServers\": {\n \"mcp-server-datadog\": {\n \"command\": \"npx\",\n \"args\": [\"-y\", \"@winor30/mcp-server-datadog\"],\n \"env\": {\n \"DATADOG_API_KEY\": \"\",\n \"DATADOG_APP_KEY\": \"\",\n \"DATADOG_SITE\": \"\" // Optional\n }\n }\n }\n}\n```\n\n## Debugging\n\nBecause MCP servers communicate over standard input/output, debugging can sometimes be tricky. We recommend using the [MCP Inspector](https://github.com/modelcontextprotocol/inspector). You can run the inspector with:\n\n```bash\nnpm run inspector\n```\n\nThe inspector will provide a URL you can open in your browser to see logs and send requests manually.\n\n## Contributing\n\nContributions are welcome! Feel free to open an issue or a pull request if you have any suggestions, bug reports, or improvements to propose.\n\n## License\n\nThis project is licensed under the [Apache License, Version 2.0](./LICENSE).\n","English","tag","en-US",{"_29":41,"_33":44,"_38":45},{"_31":42,"_33":34,"_35":43},"El servidor MCP proporciona una interfaz con la API de Datadog, lo que permite una gestión fluida de incidentes, monitorización, registros, paneles, métricas, seguimientos y hosts. Su diseño extensible facilita la integración de otras API de Datadog para futuras expansiones.","# Servidor MCP de Datadog\n\n> **DESCARGO DE RESPONSABILIDAD** : Este es un proyecto mantenido por la comunidad y no está afiliado oficialmente con, respaldado por, ni respaldado por Datadog, Inc. Este servidor MCP utiliza la API de Datadog, pero se desarrolla de forma independiente como parte del ecosistema [del Protocolo de contexto de modelo](https://github.com/modelcontextprotocol/servers) .\n\n![Versión NPM](https://img.shields.io/npm/v/%40winor30%2Fmcp-server-datadog)![Construir y probar](https://github.com/winor30/mcp-server-datadog/actions/workflows/ci.yml/badge.svg) [![código decodificador](https://codecov.io/gh/winor30/mcp-server-datadog/graph/badge.svg?token=BG4ZB74X92)](https://codecov.io/gh/winor30/mcp-server-datadog) [![insignia de herrería](https://smithery.ai/badge/@winor30/mcp-server-datadog)](https://smithery.ai/server/@winor30/mcp-server-datadog)\n\nServidor MCP para la API de Datadog, que permite la gestión de incidentes y más.\n\n## Características\n\n* **Herramientas de observación** : proporciona un mecanismo para aprovechar las funciones clave de monitoreo de Datadog, como incidentes, monitores, registros, paneles y métricas, a través del servidor MCP.\n* **Diseño extensible** : diseñado para integrarse fácilmente con API adicionales de Datadog, lo que permite una expansión de funciones futuras sin inconvenientes.\n\n## Herramientas\n\n1. `list_incidents`\n\n * Recupere una lista de incidentes de Datadog.\n * **Entradas** :\n * `filter` (cadena opcional): parámetros de filtro para incidentes (por ejemplo, estado, prioridad).\n * `pagination` (objeto opcional): Detalles de paginación como tamaño/desplazamiento de la página.\n * **Devuelve** : Matriz de incidentes de Datadog y metadatos asociados.\n\n2. `get_incident`\n\n * Recupere información detallada sobre un incidente específico de Datadog.\n * **Entradas** :\n * `incident_id` (cadena): ID del incidente del que se obtendrán detalles.\n * **Devuelve** : Información detallada del incidente (título, estado, marcas de tiempo, etc.).\n\n3. `get_monitors`\n\n * Obtener el estado de los monitores Datadog.\n * **Entradas** :\n * `groupStates` (matriz opcional): estados para filtrar (por ejemplo, alerta, advertir, sin datos, ok).\n * `name` (cadena opcional): filtrar por nombre.\n * `tags` (matriz opcional): filtrar por etiquetas.\n * **Devuelve** : Monitorea datos y un resumen de sus estados.\n\n4. `get_logs`\n\n * Busque y recupere registros de Datadog.\n * **Entradas** :\n * `query` (cadena): Datadog registra la cadena de consulta.\n * `from` (número): Hora de inicio en segundos de época.\n * `to` (número): Hora de finalización en segundos de época.\n * `limit` (número opcional): número máximo de registros a devolver (predeterminado 100).\n * **Devuelve** : Matriz de registros coincidentes.\n\n5. `list_dashboards`\n\n * Obtenga una lista de paneles de Datadog.\n * **Entradas** :\n * `name` (cadena opcional): filtra los paneles por nombre.\n * `tags` (matriz opcional): filtra los paneles por etiquetas.\n * **Devuelve** : Matriz de paneles con referencias URL.\n\n6. `get_dashboard`\n\n * Recupere un panel específico de Datadog.\n * **Entradas** :\n * `dashboard_id` (cadena): ID del panel a recuperar.\n * **Devuelve** : Detalles del panel, incluido título, widgets, etc.\n\n7. `query_metrics`\n\n * Recupere datos de métricas de Datadog.\n * **Entradas** :\n * `query` (cadena): cadena de consulta de métricas.\n * `from` (número): Hora de inicio en segundos de época.\n * `to` (número): Hora de finalización en segundos de época.\n * **Devuelve** : datos métricos para el período de tiempo consultado.\n\n8. `list_traces`\n\n * Recupere una lista de seguimientos de APM de Datadog.\n * **Entradas** :\n * `query` (cadena): cadena de consulta de seguimiento de Datadog APM.\n * `from` (número): Hora de inicio en segundos de época.\n * `to` (número): Hora de finalización en segundos de época.\n * `limit` (número opcional): número máximo de seguimientos a devolver (predeterminado 100).\n * `sort` (cadena opcional): orden de clasificación de los seguimientos (el valor predeterminado es '-timestamp').\n * `service` (cadena opcional): filtrar por nombre de servicio.\n * `operation` (cadena opcional): filtrar por nombre de operación.\n * **Devuelve** : Matriz de seguimientos coincidentes de Datadog APM.\n\n9. `list_hosts`\n\n * Obtenga la lista de hosts de Datadog.\n * **Entradas** :\n * `filter` (cadena opcional): cadena de filtro para los resultados de búsqueda.\n * `sort_field` (cadena opcional): Campo para ordenar los hosts.\n * `sort_dir` (cadena opcional): Dirección de ordenación (asc/desc).\n * `start` (número opcional): Desplazamiento inicial para la paginación.\n * `count` (número opcional): número máximo de hosts a devolver (máximo: 1000).\n * `from` (número opcional): busca hosts desde esta marca de tiempo de UNIX.\n * `include_muted_hosts_data` (booleano opcional): incluye el estado y la expiración de los hosts silenciados.\n * `include_hosts_metadata` (booleano opcional): incluye metadatos del host (versión, plataforma, etc.).\n * **Devuelve** : Matriz de hosts con detalles que incluyen nombre, ID, alias, aplicaciones, estado de silencio y más.\n\n10. `get_active_hosts_count`\n\n* Obtenga el número total de hosts activos en Datadog.\n* **Entradas** :\n * `from` (número opcional): Número de segundos a partir del cual desea obtener el número total de hosts activos (el valor predeterminado es 2 h).\n* **Devuelve** : recuento del total de hosts activos y activos.\n\n11. `mute_host`\n\n* Silenciar un host en Datadog.\n* **Entradas** :\n * `hostname` (cadena): el nombre del host que se silenciará.\n * `message` (cadena opcional): Mensaje a asociar con el silenciamiento de este host.\n * `end` (número opcional): marca de tiempo POSIX que indica cuándo debe finalizar el silencio.\n * `override` (booleano opcional): si es verdadero y el host ya está silenciado, reemplaza la hora de finalización existente.\n* **Devuelve** : Estado de éxito y mensaje de confirmación.\n\n12. `unmute_host`\n\n* Activar el silencio de un host en Datadog.\n* **Entradas** :\n * `hostname` (cadena): el nombre del host cuyo sonido se va a anular.\n* **Devuelve** : Estado de éxito y mensaje de confirmación.\n\n13. `list_downtimes`\n\n* Enumere los tiempos de inactividad programados de Datadog.\n* **Entradas** :\n * `currentOnly` (booleano opcional): devuelve solo los tiempos de inactividad actualmente activos cuando es verdadero.\n * `monitorId` (número opcional): filtrar por ID de monitor.\n* **Devoluciones** : Matriz de tiempos de inactividad programados con detalles que incluyen alcance, información del monitor y cronograma.\n\n14. `schedule_downtime`\n\n* Programe un tiempo de inactividad en Datadog.\n* **Entradas** :\n * `scope` (cadena): Ámbito al que se aplicará el tiempo de inactividad (por ejemplo, 'host:my-host').\n * `start` (número opcional): marca de tiempo de UNIX para el inicio del tiempo de inactividad.\n * `end` (número opcional): marca de tiempo de UNIX para el final del tiempo de inactividad.\n * `message` (cadena opcional): un mensaje para incluir con el tiempo de inactividad.\n * `timezone` (cadena opcional): la zona horaria para el tiempo de inactividad (por ejemplo, 'UTC', 'América/Nueva\\_York').\n * `monitorId` (número opcional): el ID del monitor a silenciar.\n * `monitorTags` (matriz opcional): una lista de etiquetas de monitor para filtrar.\n * `recurrence` (objeto opcional): configuración de recurrencia para el tiempo de inactividad.\n * `type` (cadena): Tipo de recurrencia ('días', 'semanas', 'meses', 'años').\n * `period` (número): con qué frecuencia repetir (debe ser >= 1).\n * `weekDays` (matriz opcional): días de la semana para la recurrencia semanal.\n * `until` (número opcional): marca de tiempo UNIX para cuando finaliza la recurrencia.\n* **Devoluciones** : Detalles del tiempo de inactividad programado, incluida la identificación y el estado activo.\n\n15. `cancel_downtime`\n\n* Cancelar un tiempo de inactividad programado en Datadog.\n* **Entradas** :\n * `downtimeId` (número): el ID del tiempo de inactividad que se cancelará.\n* **Devoluciones** : Confirmación de cancelación del tiempo de inactividad.\n\n16. `get_rum_applications`\n\n* Obtenga todas las aplicaciones RUM en la organización.\n* **Entradas** : Ninguna.\n* **Devuelve** : Lista de aplicaciones RUM.\n\n17. `get_rum_events`\n\n* Busque y recupere eventos RUM de Datadog.\n* **Entradas** :\n * `query` (cadena): cadena de consulta de Datadog RUM.\n * `from` (número): Hora de inicio en segundos de época.\n * `to` (número): Hora de finalización en segundos de época.\n * `limit` (número opcional): número máximo de eventos a devolver (predeterminado: 100).\n* **Devuelve** : Matriz de eventos RUM.\n\n18. `get_rum_grouped_event_count`\n\n* Busque, agrupar y contar eventos RUM según una dimensión específica.\n* **Entradas** :\n * `query` (cadena opcional): filtro de consulta adicional para la búsqueda de RUM (predeterminado: \"\\*\").\n * `from` (número): Hora de inicio en segundos de época.\n * `to` (número): Hora de finalización en segundos de época.\n * `groupBy` (cadena opcional): dimensión para agrupar los resultados por (valor predeterminado: \"application.name\").\n* **Devuelve** : recuentos de eventos agrupados.\n\n19. `get_rum_page_performance`\n\n* Obtenga métricas de rendimiento de página (vista) a partir de los datos de RUM.\n* **Entradas** :\n * `query` (cadena opcional): filtro de consulta adicional para la búsqueda de RUM (predeterminado: \"\\*\").\n * `from` (número): Hora de inicio en segundos de época.\n * `to` (número): Hora de finalización en segundos de época.\n * `metricNames` (matriz de cadenas): matriz de nombres de métricas para recuperar (por ejemplo, 'view.load\\_time', 'view.first\\_contentful\\_paint').\n* **Devoluciones** : métricas de rendimiento que incluyen promedio, mínimo, máximo y recuento para cada métrica.\n\n20. `get_rum_page_waterfall`\n\n* Recupere datos de cascada de la página RUM (vista) filtrados por nombre de aplicación e ID de sesión.\n* **Entradas** :\n * `applicationName` (cadena): nombre de la aplicación para filtrar eventos.\n * `sessionId` (cadena): ID de sesión para filtrar eventos.\n* **Devuelve** : datos en cascada para la aplicación y sesión especificadas.\n\n## Configuración\n\n### Credenciales de Datadog\n\nNecesita credenciales de API de Datadog válidas para usar este servidor MCP:\n\n* `DATADOG_API_KEY` : Su clave API de Datadog\n* `DATADOG_APP_KEY` : Su clave de aplicación Datadog\n* `DATADOG_SITE` (opcional): El sitio de Datadog (por ejemplo `datadoghq.eu` )\n\nExportelos a su entorno antes de ejecutar el servidor:\n\n```bash\nexport DATADOG_API_KEY=\"your_api_key\"\nexport DATADOG_APP_KEY=\"your_app_key\"\nexport DATADOG_SITE=\"your_datadog_site\"\n```\n\n## Instalación\n\n### Instalación mediante herrería\n\nPara instalar Datadog MCP Server para Claude Desktop automáticamente a través de [Smithery](https://smithery.ai/server/@winor30/mcp-server-datadog) :\n\n```bash\nnpx -y @smithery/cli install @winor30/mcp-server-datadog --client claude\n```\n\n### Instalación manual\n\n```bash\npnpm install\npnpm build\npnpm watch # for development with auto-rebuild\n```\n\n## Uso con Claude Desktop\n\nPara usar esto con Claude Desktop, agregue lo siguiente a su `claude_desktop_config.json` :\n\nEn MacOS: `~/Library/Application Support/Claude/claude_desktop_config.json`\\\nEn Windows: `%APPDATA%/Claude/claude_desktop_config.json`\n\n```json\n{\n \"mcpServers\": {\n \"github\": {\n \"command\": \"npx\",\n \"args\": [\"-y\", \"@modelcontextprotocol/server-github\"],\n \"env\": {\n \"GITHUB_PERSONAL_ACCESS_TOKEN\": \"\"\n }\n }\n }\n}\n```\n\n```json\n{\n \"mcpServers\": {\n \"datadog\": {\n \"command\": \"/path/to/mcp-server-datadog/build/index.js\",\n \"env\": {\n \"DATADOG_API_KEY\": \"\",\n \"DATADOG_APP_KEY\": \"\",\n \"DATADOG_SITE\": \"\" // Optional\n }\n }\n }\n}\n```\n\nO especifique a través de `npx` :\n\n```json\n{\n \"mcpServers\": {\n \"mcp-server-datadog\": {\n \"command\": \"npx\",\n \"args\": [\"-y\", \"@winor30/mcp-server-datadog\"],\n \"env\": {\n \"DATADOG_API_KEY\": \"\",\n \"DATADOG_APP_KEY\": \"\",\n \"DATADOG_SITE\": \"\" // Optional\n }\n }\n }\n}\n```\n\n## Depuración\n\nDado que los servidores MCP se comunican mediante E/S estándar, la depuración a veces puede ser complicada. Recomendamos usar el [Inspector MCP](https://github.com/modelcontextprotocol/inspector) . Puede ejecutar el inspector con:\n\n```bash\nnpm run inspector\n```\n\nEl inspector le proporcionará una URL que podrá abrir en su navegador para ver registros y enviar solicitudes manualmente.\n\n## Contribuyendo\n\n¡Agradecemos sus contribuciones! Si tiene alguna sugerencia, informe de errores o propuesta de mejora, no dude en abrir un problema o una solicitud de incorporación de cambios.\n\n## Licencia\n\nEste proyecto está licenciado bajo la [Licencia Apache, Versión 2.0](./LICENSE) .","Spanish","es-ES",{"_29":47,"_33":50,"_38":51},{"_31":48,"_33":34,"_35":49},"MCPサーバーはDatadog APIへのインターフェースを提供し、インシデント、監視、ログ、ダッシュボード、メトリクス、トレース、ホストのシームレスな管理を可能にします。拡張性の高い設計により、将来の拡張に備えて追加のDatadog APIを容易に統合できます。","# Datadog MCP サーバー\n\n> **免責事項**：これはコミュニティによって管理されているプロジェクトであり、Datadog, Inc. と正式に提携、承認、またはサポートされていません。この MCP サーバーは Datadog API を利用しますが、 [Model Context Protocol エコ](https://github.com/modelcontextprotocol/servers)システムの一部として独立して開発されています。\n\n![NPMバージョン](https://img.shields.io/npm/v/%40winor30%2Fmcp-server-datadog)![ビルドとテスト](https://github.com/winor30/mcp-server-datadog/actions/workflows/ci.yml/badge.svg) [![コードコフ](https://codecov.io/gh/winor30/mcp-server-datadog/graph/badge.svg?token=BG4ZB74X92)](https://codecov.io/gh/winor30/mcp-server-datadog) [![鍛冶屋のバッジ](https://smithery.ai/badge/@winor30/mcp-server-datadog)](https://smithery.ai/server/@winor30/mcp-server-datadog)\n\nインシデント管理などを可能にする、Datadog API 用の MCP サーバー。\n\n## 特徴\n\n* **観測可能性ツール**: MCP サーバーを通じて、インシデント、モニター、ログ、ダッシュボード、メトリックなどの主要な Datadog 監視機能を活用するためのメカニズムを提供します。\n* **拡張可能な設計**: 追加の Datadog API と簡単に統合できるように設計されており、将来の機能拡張をシームレスに行うことができます。\n\n## ツール\n\n1. `list_incidents`\n\n * Datadog からインシデントのリストを取得します。\n * **入力**:\n * `filter` (オプションの文字列): インシデントのフィルターパラメータ (例: ステータス、優先度)。\n * `pagination` (オプションオブジェクト): ページサイズやオフセットなどのページ区切りの詳細。\n * **戻り値**: Datadog インシデントおよび関連メタデータの配列。\n\n2. `get_incident`\n\n * 特定の Datadog インシデントに関する詳細情報を取得します。\n * **入力**:\n * `incident_id` (文字列): 詳細を取得するインシデント ID。\n * **返されるもの**: 詳細なインシデント情報 (タイトル、ステータス、タイムスタンプなど)。\n\n3. `get_monitors`\n\n * Datadog モニターのステータスを取得します。\n * **入力**:\n * `groupStates` (オプションの配列): フィルタリングする状態 (例: アラート、警告、データなし、OK)。\n * `name` (オプションの文字列): 名前でフィルタリングします。\n * `tags` (オプションの配列): タグでフィルタリングします。\n * **戻り値**: モニターのデータとそのステータスの概要。\n\n4. `get_logs`\n\n * Datadog からログを検索して取得します。\n * **入力**:\n * `query` (文字列): Datadog はクエリ文字列を記録します。\n * `from` (数値): エポック秒単位での開始時刻。\n * `to` (数値): エポック秒単位での終了時間。\n * `limit` (オプションの数値): 返されるログの最大数 (デフォルトは 100)。\n * **戻り値**: 一致するログの配列。\n\n5. `list_dashboards`\n\n * Datadog からダッシュボードのリストを取得します。\n * **入力**:\n * `name` (オプションの文字列): ダッシュボードを名前でフィルタリングします。\n * `tags` (オプションの配列): タグでダッシュボードをフィルタリングします。\n * **戻り値**: URL 参照を含むダッシュボードの配列。\n\n6. `get_dashboard`\n\n * Datadog から特定のダッシュボードを取得します。\n * **入力**:\n * `dashboard_id` (文字列): 取得するダッシュボードの ID。\n * **戻り値**: タイトル、ウィジェットなどのダッシュボードの詳細。\n\n7. `query_metrics`\n\n * Datadog からメトリクスデータを取得します。\n * **入力**:\n * `query` (文字列): メトリクスクエリ文字列。\n * `from` (数値): エポック秒単位での開始時刻。\n * `to` (数値): エポック秒単位での終了時間。\n * **戻り値**: 照会された時間枠のメトリックデータ。\n\n8. `list_traces`\n\n * Datadog から APM トレースのリストを取得します。\n * **入力**:\n * `query` (文字列): Datadog APM トレースクエリ文字列。\n * `from` (数値): エポック秒単位での開始時刻。\n * `to` (数値): エポック秒単位での終了時間。\n * `limit` (オプションの数値): 返されるトレースの最大数 (デフォルトは 100)。\n * `sort` (オプションの文字列): トレースのソート順序 (デフォルトは '-timestamp')。\n * `service` (オプションの文字列): サービス名でフィルタリングします。\n * `operation` (オプションの文字列): 操作名でフィルタリングします。\n * **戻り値**: Datadog APM からの一致するトレースの配列。\n\n9. `list_hosts`\n\n * Datadog からホストのリストを取得します。\n * **入力**:\n * `filter` (オプションの文字列): 検索結果のフィルター文字列。\n * `sort_field` (オプションの文字列): ホストを並べ替えるフィールド。\n * `sort_dir` (オプションの文字列): 並べ替えの方向 (昇順/降順)。\n * `start` (オプションの数値): ページ区切りの開始オフセット。\n * `count` (オプションの数値): 返されるホストの最大数 (最大: 1000)。\n * `from` (オプションの数値): この UNIX タイムスタンプからホストを検索します。\n * `include_muted_hosts_data` (オプションのブール値): ミュートされたホストのステータスと有効期限を含めます。\n * `include_hosts_metadata` (オプションのブール値): ホストのメタデータ (バージョン、プラットフォームなど) を含めます。\n * **戻り値**: 名前、ID、エイリアス、アプリ、ミュートステータスなどの詳細を含むホストの配列。\n\n10. `get_active_hosts_count`\n\n* Datadog 内のアクティブなホストの合計数を取得します。\n* **入力**:\n * `from` (オプションの数値): アクティブなホストの合計数を取得する秒数 (デフォルトは 2 時間)。\n* **返される値**: アクティブで稼働中のホストの合計数。\n\n11. `mute_host`\n\n* Datadog でホストをミュートします。\n* **入力**:\n * `hostname` (文字列): ミュートするホストの名前。\n * `message` (オプションの文字列): このホストのミュートに関連付けるメッセージ。\n * `end` (オプションの数値): ミュートを終了するタイミングを示す POSIX タイムスタンプ。\n * `override` (オプションのブール値): true で、ホストがすでにミュートされている場合は、既存の終了時刻を置き換えます。\n* **戻り値**: 成功ステータスと確認メッセージ。\n\n12. `unmute_host`\n\n* Datadog でホストのミュートを解除します。\n* **入力**:\n * `hostname` (文字列): ミュート解除するホストの名前。\n* **戻り値**: 成功ステータスと確認メッセージ。\n\n13. `list_downtimes`\n\n* Datadog からのスケジュールされたダウンタイムを一覧表示します。\n* **入力**:\n * `currentOnly` (オプションのブール値): true の場合、現在アクティブなダウンタイムのみを返します。\n * `monitorId` (オプションの数値): モニター ID でフィルタリングします。\n* **戻り値**: 範囲、監視情報、スケジュールなどの詳細を含む、スケジュールされたダウンタイムの配列。\n\n14. `schedule_downtime`\n\n* Datadog でダウンタイムをスケジュールします。\n* **入力**:\n * `scope` (文字列): ダウンタイムを適用するスコープ (例: 'host:my-host')。\n * `start` (オプションの数値): ダウンタイムの開始の UNIX タイムスタンプ。\n * `end` (オプションの数値): ダウンタイムの終了を示す UNIX タイムスタンプ。\n * `message` (オプションの文字列): ダウンタイムに含めるメッセージ。\n * `timezone` (オプションの文字列): ダウンタイムのタイムゾーン (例: 'UTC'、'America/New\\_York')。\n * `monitorId` (オプションの数値): ミュートするモニターの ID。\n * `monitorTags` (オプションの配列): フィルタリングするモニタータグのリスト。\n * `recurrence` (オプションオブジェクト): ダウンタイムの繰り返し設定。\n * `type` (文字列): 繰り返しの種類 ('days'、'weeks'、'months'、'years')。\n * `period` （数値）：繰り返す頻度（1 以上である必要があります）。\n * `weekDays` (オプションの配列): 毎週繰り返す曜日。\n * `until` (オプションの数値): 繰り返しが終了する時点の UNIX タイムスタンプ。\n* **返される値**: ID およびアクティブステータスを含む、スケジュールされたダウンタイムの詳細。\n\n15. `cancel_downtime`\n\n* Datadog でスケジュールされたダウンタイムをキャンセルします。\n* **入力**:\n * `downtimeId` (数値): キャンセルするダウンタイムの ID。\n* **戻り値**: ダウンタイムキャンセルの確認。\n\n16. `get_rum_applications`\n\n* 組織内のすべての RUM アプリケーションを取得します。\n* **入力**: なし。\n* **返される値**: RUM アプリケーションのリスト。\n\n17. `get_rum_events`\n\n* Datadog から RUM イベントを検索して取得します。\n* **入力**:\n * `query` (文字列): Datadog RUM クエリ文字列。\n * `from` (数値): エポック秒単位での開始時刻。\n * `to` (数値): エポック秒単位での終了時間。\n * `limit` (オプションの数値): 返されるイベントの最大数 (デフォルト: 100)。\n* **戻り値**: RUM イベントの配列。\n\n18. `get_rum_grouped_event_count`\n\n* 指定されたディメンションで RUM イベントを検索、グループ化、カウントします。\n* **入力**:\n * `query` (オプションの文字列): RUM 検索の追加クエリフィルター (デフォルト: \"\\*\")。\n * `from` (数値): エポック秒単位での開始時刻。\n * `to` (数値): エポック秒単位での終了時間。\n * `groupBy` (オプションの文字列): 結果をグループ化するディメンション (デフォルト: \"application.name\")。\n* **戻り値**: グループ化されたイベント数。\n\n19. `get_rum_page_performance`\n\n* RUM データからページ (ビュー) のパフォーマンスメトリックを取得します。\n* **入力**:\n * `query` (オプションの文字列): RUM 検索の追加クエリフィルター (デフォルト: \"\\*\")。\n * `from` (数値): エポック秒単位での開始時刻。\n * `to` (数値): エポック秒単位での終了時間。\n * `metricNames` (文字列の配列): 取得するメトリック名の配列 (例: 'view.load\\_time'、'view.first\\_contentful\\_paint')。\n* **返される値**: 各メトリックの平均、最小、最大、カウントなどのパフォーマンスメトリック。\n\n20. `get_rum_page_waterfall`\n\n* アプリケーション名とセッション ID でフィルタリングされた RUM ページ (ビュー) のウォーターフォールデータを取得します。\n* **入力**:\n * `applicationName` (文字列): イベントをフィルタリングするアプリケーション名。\n * `sessionId` (文字列): イベントをフィルタリングするセッション ID。\n* **戻り値**: 指定されたアプリケーションとセッションのウォーターフォールデータ。\n\n## 設定\n\n### Datadog の認証情報\n\nこの MCP サーバーを使用するには、有効な Datadog API 認証情報が必要です。\n\n* `DATADOG_API_KEY` : Datadog APIキー\n* `DATADOG_APP_KEY` : Datadog アプリケーションキー\n* `DATADOG_SITE` (オプション): Datadog サイト (例: `datadoghq.eu` )\n\nサーバーを実行する前に、それらを環境にエクスポートします。\n\n```bash\nexport DATADOG_API_KEY=\"your_api_key\"\nexport DATADOG_APP_KEY=\"your_app_key\"\nexport DATADOG_SITE=\"your_datadog_site\"\n```\n\n## インストール\n\n### Smithery経由でインストール\n\n[Smithery](https://smithery.ai/server/@winor30/mcp-server-datadog)経由で Claude Desktop 用の Datadog MCP Server を自動的にインストールするには:\n\n```bash\nnpx -y @smithery/cli install @winor30/mcp-server-datadog --client claude\n```\n\n### 手動インストール\n\n```bash\npnpm install\npnpm build\npnpm watch # for development with auto-rebuild\n```\n\n## Claude Desktopでの使用\n\nClaude Desktop でこれを使用するには、 `claude_desktop_config.json`に以下を追加します。\n\nMacOSの場合: `~/Library/Application Support/Claude/claude_desktop_config.json`\\\nWindows の場合: `%APPDATA%/Claude/claude_desktop_config.json`\n\n```json\n{\n \"mcpServers\": {\n \"github\": {\n \"command\": \"npx\",\n \"args\": [\"-y\", \"@modelcontextprotocol/server-github\"],\n \"env\": {\n \"GITHUB_PERSONAL_ACCESS_TOKEN\": \"\"\n }\n }\n }\n}\n```\n\n```json\n{\n \"mcpServers\": {\n \"datadog\": {\n \"command\": \"/path/to/mcp-server-datadog/build/index.js\",\n \"env\": {\n \"DATADOG_API_KEY\": \"\",\n \"DATADOG_APP_KEY\": \"\",\n \"DATADOG_SITE\": \"\" // Optional\n }\n }\n }\n}\n```\n\nまたは`npx`で指定します:\n\n```json\n{\n \"mcpServers\": {\n \"mcp-server-datadog\": {\n \"command\": \"npx\",\n \"args\": [\"-y\", \"@winor30/mcp-server-datadog\"],\n \"env\": {\n \"DATADOG_API_KEY\": \"\",\n \"DATADOG_APP_KEY\": \"\",\n \"DATADOG_SITE\": \"\" // Optional\n }\n }\n }\n}\n```\n\n## デバッグ\n\nMCPサーバーは標準入出力を介して通信するため、デバッグが難しくなる場合があります。MCP [Inspector の](https://github.com/modelcontextprotocol/inspector)使用をお勧めします。Inspectorは次のコマンドで実行できます。\n\n```bash\nnpm run inspector\n```\n\nインスペクターは、ブラウザで開いてログを表示したり、リクエストを手動で送信したりできる URL を提供します。\n\n## 貢献\n\n貢献を歓迎します！ご提案、バグ報告、改善提案などございましたら、お気軽に問題報告またはプルリクエストをご提出ください。\n\n## ライセンス\n\nこのプロジェクトは[、Apache License バージョン 2.0](./LICENSE)に基づいてライセンスされます。","Japanese","ja-JP",{"_29":53,"_33":57,"_38":58},{"_31":54,"_33":55,"_35":56},"MCP 서버는 Datadog API에 대한 인터페이스를 제공하여 인시던트, 모니터링, 로그, 대시보드, 메트릭, 추적 및 호스트를 원활하게 관리할 수 있도록 합니다. 확장 가능한 설계 덕분에 향후 확장을 위해 추가 Datadog API를 쉽게 통합할 수 있습니다.","mcp-서버-데이터독","# Datadog MCP 서버\n\n> **면책 조항** : 이것은 커뮤니티에서 유지하는 프로젝트이며 Datadog, Inc.와 공식적으로 제휴, 보증 또는 지원을 받지 않습니다. 이 MCP 서버는 Datadog API를 활용하지만 [Model Context Protocol](https://github.com/modelcontextprotocol/servers) 생태계의 일부로 독립적으로 개발되었습니다.\n\n![NPM 버전](https://img.shields.io/npm/v/%40winor30%2Fmcp-server-datadog)![빌드 및 테스트](https://github.com/winor30/mcp-server-datadog/actions/workflows/ci.yml/badge.svg) [![코드코브](https://codecov.io/gh/winor30/mcp-server-datadog/graph/badge.svg?token=BG4ZB74X92)](https://codecov.io/gh/winor30/mcp-server-datadog) [![대장간 배지](https://smithery.ai/badge/@winor30/mcp-server-datadog)](https://smithery.ai/server/@winor30/mcp-server-datadog)\n\nDatadog API를 위한 MCP 서버로, 사고 관리 등을 가능하게 합니다.\n\n## 특징\n\n* **관찰 도구** : MCP 서버를 통해 인시던트, 모니터, 로그, 대시보드, 지표와 같은 주요 Datadog 모니터링 기능을 활용할 수 있는 메커니즘을 제공합니다.\n* **확장 가능한 디자인** : 추가적인 Datadog API와 쉽게 통합되도록 설계되어 향후 기능 확장이 원활합니다.\n\n## 도구\n\n1. `list_incidents`\n\n * Datadog에서 사건 목록을 검색합니다.\n * **입력** :\n * `filter` (선택적 문자열): 사고에 대한 필터 매개변수(예: 상태, 우선순위).\n * `pagination` (선택적 객체): 페이지 크기/오프셋과 같은 페이지 번호 매기기 세부 정보입니다.\n * **반환값** : Datadog 사건 및 관련 메타데이터의 배열입니다.\n\n2. `get_incident`\n\n * 특정 Datadog 사건에 대한 자세한 정보를 검색합니다.\n * **입력** :\n * `incident_id` (문자열): 세부 정보를 가져올 사건 ID입니다.\n * **반환** : 자세한 사고 정보(제목, 상태, 타임스탬프 등)\n\n3. `get_monitors`\n\n * Datadog 모니터의 상태를 가져옵니다.\n * **입력** :\n * `groupStates` (선택적 배열): 필터링할 상태(예: 경고, 경고, 데이터 없음, 확인).\n * `name` (선택 문자열): 이름으로 필터링합니다.\n * `tags` (선택적 배열): 태그로 필터링합니다.\n * **반환** : 데이터와 상태 요약을 모니터링합니다.\n\n4. `get_logs`\n\n * Datadog에서 로그를 검색하고 불러옵니다.\n * **입력** :\n * `query` (문자열): Datadog 로그 쿼리 문자열입니다.\n * ( `from` ): 시작 시간(에포크 초)입니다.\n * (숫자): 종료 시간(에포크 초) `to` .\n * `limit` (선택적 숫자): 반환할 로그의 최대 개수(기본값은 100).\n * **반환값** : 일치하는 로그 배열입니다.\n\n5. `list_dashboards`\n\n * Datadog에서 대시보드 목록을 가져옵니다.\n * **입력** :\n * `name` (선택 문자열): 이름으로 대시보드를 필터링합니다.\n * `tags` (선택적 배열): 태그로 대시보드를 필터링합니다.\n * **반환** : URL 참조가 있는 대시보드 배열입니다.\n\n6. `get_dashboard`\n\n * Datadog에서 특정 대시보드를 검색합니다.\n * **입력** :\n * `dashboard_id` (문자열): 가져올 대시보드의 ID입니다.\n * **반환** : 제목, 위젯 등을 포함한 대시보드 세부 정보\n\n7. `query_metrics`\n\n * Datadog에서 메트릭 데이터를 검색합니다.\n * **입력** :\n * `query` (문자열): 메트릭 쿼리 문자열.\n * ( `from` ): 시작 시간(에포크 초)입니다.\n * (숫자): 종료 시간(에포크 초) `to` .\n * **반환** : 쿼리된 기간에 대한 메트릭 데이터입니다.\n\n8. `list_traces`\n\n * Datadog에서 APM 추적 목록을 검색합니다.\n * **입력** :\n * `query` (문자열): Datadog APM 추적 쿼리 문자열.\n * ( `from` ): 시작 시간(에포크 초)입니다.\n * (숫자): 종료 시간(에포크 초) `to` .\n * `limit` (선택적 숫자): 반환할 추적의 최대 수(기본값은 100).\n * `sort` (선택적 문자열): 추적에 대한 정렬 순서(기본값은 '-timestamp').\n * `service` (선택 문자열): 서비스 이름으로 필터링합니다.\n * `operation` (선택 문자열): 작업 이름으로 필터링합니다.\n * **반환** : Datadog APM의 일치하는 추적 배열입니다.\n\n9. `list_hosts`\n\n * Datadog에서 호스트 목록을 가져옵니다.\n * **입력** :\n * `filter` (선택 문자열): 검색 결과에 대한 필터 문자열입니다.\n * `sort_field` (선택적 문자열): 호스트를 정렬할 필드입니다.\n * `sort_dir` (선택적 문자열): 정렬 방향(오름차순/내림차순).\n * `start` (선택적 숫자): 페이지 매김을 위한 시작 오프셋입니다.\n * `count` (선택적 숫자): 반환할 호스트의 최대 수(최대: 1000).\n * `from` (선택적 숫자): 이 UNIX 타임스탬프에서 호스트를 검색합니다.\n * `include_muted_hosts_data` (선택적 부울): 음소거된 호스트 상태 및 만료를 포함합니다.\n * `include_hosts_metadata` (선택적 부울): 호스트 메타데이터(버전, 플랫폼 등)를 포함합니다.\n * **반환** : 이름, ID, 별칭, 앱, 음소거 상태 등의 세부 정보가 포함된 호스트 배열입니다.\n\n10. `get_active_hosts_count`\n\n* Datadog에서 활성 호스트의 총 수를 가져옵니다.\n* **입력** :\n * (선택적 숫자): 활성 호스트의 총 수를 가져올 시작 시간(초) `from` (기본값은 2시간).\n* **반환값** : 활성 호스트와 가동 중인 호스트의 총 개수입니다.\n\n11. `mute_host`\n\n* Datadog에서 호스트를 음소거합니다.\n* **입력** :\n * `hostname` (문자열): 음소거할 호스트의 이름입니다.\n * `message` (선택적 문자열): 이 호스트의 음소거와 관련된 메시지입니다.\n * `end` (선택적 숫자): 음소거가 종료되어야 하는 POSIX 타임스탬프입니다.\n * `override` (선택적 부울): true이고 호스트가 이미 음소거된 경우 기존 종료 시간을 대체합니다.\n* **반환** : 성공 상태 및 확인 메시지.\n\n12. `unmute_host`\n\n* Datadog에서 호스트의 음소거를 해제합니다.\n* **입력** :\n * `hostname` (문자열): 음소거를 해제할 호스트의 이름입니다.\n* **반환** : 성공 상태 및 확인 메시지.\n\n13. `list_downtimes`\n\n* Datadog에서 예정된 다운타임을 나열합니다.\n* **입력** :\n * `currentOnly` (선택적 부울): true인 경우 현재 활성화된 다운타임만 반환합니다.\n * `monitorId` (선택적 숫자): 모니터 ID로 필터링합니다.\n* **반환** : 범위, 모니터 정보, 일정을 포함한 세부 정보가 포함된 예정된 가동 중지 시간의 배열입니다.\n\n14. `schedule_downtime`\n\n* Datadog에서 다운타임을 예약하세요.\n* **입력** :\n * `scope` (문자열): 가동 중지 시간을 적용할 범위(예: 'host:my-host').\n * `start` (선택적 숫자): 다운타임 시작을 나타내는 UNIX 타임스탬프입니다.\n * `end` (선택적 숫자): 다운타임 종료를 나타내는 UNIX 타임스탬프입니다.\n * `message` (선택적 문자열): 다운타임에 포함할 메시지입니다.\n * `timezone` (선택적 문자열): 가동 중지 시간의 시간대(예: 'UTC', 'America/New\\_York').\n * `monitorId` (선택적 숫자): 음소거할 모니터의 ID입니다.\n * `monitorTags` (선택적 배열): 필터링을 위한 모니터 태그 목록입니다.\n * `recurrence` (선택적 객체): 다운타임에 대한 반복 설정입니다.\n * `type` (문자열): 반복 유형('일', '주', '월', '년').\n * `period` (숫자): 반복 빈도(1 이상이어야 함).\n * `weekDays` (선택적 배열): 매주 반복되는 요일입니다.\n * `until` (선택적 숫자): 반복이 종료되는 시점을 나타내는 UNIX 타임스탬프입니다.\n* **반환** : ID 및 활성 상태를 포함한 예정된 가동 중지 세부 정보.\n\n15. `cancel_downtime`\n\n* Datadog에서 예약된 다운타임을 취소합니다.\n* **입력** :\n * `downtimeId` (숫자): 취소할 다운타임의 ID입니다.\n* **반환** : 가동 중지 취소 확인.\n\n16. `get_rum_applications`\n\n* 조직 내 모든 RUM 애플리케이션을 가져옵니다.\n* **입력** : 없음.\n* **반환** : RUM 애플리케이션 목록.\n\n17. `get_rum_events`\n\n* Datadog에서 RUM 이벤트를 검색하고 불러옵니다.\n* **입력** :\n * `query` (문자열): Datadog RUM 쿼리 문자열.\n * ( `from` ): 시작 시간(에포크 초)입니다.\n * (숫자): 종료 시간(에포크 초) `to` .\n * `limit` (선택적 숫자): 반환할 이벤트의 최대 개수(기본값: 100).\n* **반환값** : RUM 이벤트 배열.\n\n18. `get_rum_grouped_event_count`\n\n* 지정된 차원별로 RUM 이벤트를 검색, 그룹화하고 계산합니다.\n* **입력** :\n * `query` (선택적 문자열): RUM 검색을 위한 추가 쿼리 필터(기본값: \"\\*\").\n * ( `from` ): 시작 시간(에포크 초)입니다.\n * (숫자): 종료 시간(에포크 초) `to` .\n * `groupBy` (선택적 문자열): 결과를 그룹화할 차원(기본값: \"application.name\").\n* **반환값** : 그룹화된 이벤트 수.\n\n19. `get_rum_page_performance`\n\n* RUM 데이터에서 페이지(뷰) 성능 측정 항목을 가져옵니다.\n* **입력** :\n * `query` (선택적 문자열): RUM 검색을 위한 추가 쿼리 필터(기본값: \"\\*\").\n * ( `from` ): 시작 시간(에포크 초)입니다.\n * (숫자): 종료 시간(에포크 초) `to` .\n * `metricNames` (문자열 배열): 검색할 메트릭 이름의 배열(예: 'view.load\\_time', 'view.first\\_contentful\\_paint').\n* **반환** : 각 메트릭에 대한 평균, 최소값, 최대값 및 개수를 포함한 성능 메트릭입니다.\n\n20. `get_rum_page_waterfall`\n\n* 애플리케이션 이름과 세션 ID로 필터링된 RUM 페이지(보기) 워터폴 데이터를 검색합니다.\n* **입력** :\n * `applicationName` (문자열): 이벤트를 필터링할 애플리케이션 이름입니다.\n * `sessionId` (문자열): 이벤트를 필터링할 세션 ID입니다.\n* **반환** : 지정된 애플리케이션 및 세션에 대한 워터폴 데이터입니다.\n\n## 설정\n\n### Datadog 자격증\n\n이 MCP 서버를 사용하려면 유효한 Datadog API 자격 증명이 필요합니다.\n\n* `DATADOG_API_KEY` : Datadog API 키\n* `DATADOG_APP_KEY` : Datadog 애플리케이션 키\n* `DATADOG_SITE` (선택 사항): Datadog 사이트(예: `datadoghq.eu` )\n\n서버를 실행하기 전에 환경으로 내보내세요.\n\n지엑스피1\n\n## 설치\n\n### Smithery를 통해 설치\n\n[Smithery를](https://smithery.ai/server/@winor30/mcp-server-datadog) 통해 Claude Desktop에 Datadog MCP 서버를 자동으로 설치하려면:\n\n```bash\nnpx -y @smithery/cli install @winor30/mcp-server-datadog --client claude\n```\n\n### 수동 설치\n\n```bash\npnpm install\npnpm build\npnpm watch # for development with auto-rebuild\n```\n\n## Claude Desktop과 함께 사용\n\nClaude Desktop과 함께 사용하려면 `claude_desktop_config.json` 에 다음을 추가하세요.\n\nMacOS의 경우: `~/Library/Application Support/Claude/claude_desktop_config.json`\\\nWindows의 경우: `%APPDATA%/Claude/claude_desktop_config.json`\n\n```json\n{\n \"mcpServers\": {\n \"github\": {\n \"command\": \"npx\",\n \"args\": [\"-y\", \"@modelcontextprotocol/server-github\"],\n \"env\": {\n \"GITHUB_PERSONAL_ACCESS_TOKEN\": \"\"\n }\n }\n }\n}\n```\n\n```json\n{\n \"mcpServers\": {\n \"datadog\": {\n \"command\": \"/path/to/mcp-server-datadog/build/index.js\",\n \"env\": {\n \"DATADOG_API_KEY\": \"\",\n \"DATADOG_APP_KEY\": \"\",\n \"DATADOG_SITE\": \"\" // Optional\n }\n }\n }\n}\n```\n\n또는 `npx` 를 통해 지정하세요:\n\n```json\n{\n \"mcpServers\": {\n \"mcp-server-datadog\": {\n \"command\": \"npx\",\n \"args\": [\"-y\", \"@winor30/mcp-server-datadog\"],\n \"env\": {\n \"DATADOG_API_KEY\": \"\",\n \"DATADOG_APP_KEY\": \"\",\n \"DATADOG_SITE\": \"\" // Optional\n }\n }\n }\n}\n```\n\n## 디버깅\n\nMCP 서버는 표준 입출력(SIO)을 통해 통신하기 때문에 디버깅이 까다로울 수 있습니다. [MCP Inspector](https://github.com/modelcontextprotocol/inspector) 사용을 권장합니다. 다음 명령어를 사용하여 Inspector를 실행할 수 있습니다.\n\n```bash\nnpm run inspector\n```\n\n검사기는 브라우저에서 열어서 로그를 확인하고 수동으로 요청을 보낼 수 있는 URL을 제공합니다.\n\n## 기여하다\n\n기여를 환영합니다! 제안, 버그 리포트, 개선 사항 등이 있으시면 이슈를 생성하거나 풀 리퀘스트를 보내주세요.\n\n## 특허\n\n이 프로젝트는 [Apache 라이선스 버전 2.0](./LICENSE) 에 따라 라이선스가 부여되었습니다.","Korean","ko-KR",{"_29":60,"_33":64,"_38":65},{"_31":61,"_33":62,"_35":63},"MCP 服务器提供 Datadog API 接口，支持无缝管理事件、监控、日志、仪表板、指标、追踪和主机。其可扩展的设计允许轻松集成其他 Datadog API，以支持未来扩展。","mcp-服务器-数据狗","# Datadog MCP 服务器\n\n> **免责声明**：这是一个社区维护的项目，与 Datadog, Inc. 没有官方关联、认可或支持。此 MCP 服务器利用 Datadog API，但作为[模型上下文协议](https://github.com/modelcontextprotocol/servers)生态系统的一部分独立开发。\n\n![NPM 版本](https://img.shields.io/npm/v/%40winor30%2Fmcp-server-datadog)![构建和测试](https://github.com/winor30/mcp-server-datadog/actions/workflows/ci.yml/badge.svg) [![代码验证](https://codecov.io/gh/winor30/mcp-server-datadog/graph/badge.svg?token=BG4ZB74X92)](https://codecov.io/gh/winor30/mcp-server-datadog) [![铁匠徽章](https://smithery.ai/badge/@winor30/mcp-server-datadog)](https://smithery.ai/server/@winor30/mcp-server-datadog)\n\nDatadog API 的 MCP 服务器，支持事件管理等。\n\n## 特征\n\n* **可观察性工具**：提供一种机制，通过 MCP 服务器利用关键 Datadog 监控功能，例如事件、监视器、日志、仪表板和指标。\n* **可扩展设计**：设计用于轻松与其他 Datadog API 集成，从而实现未来的无缝功能扩展。\n\n## 工具\n\n1. `list_incidents`\n\n * 从 Datadog 检索事件列表。\n * **输入**：\n * `filter` （可选字符串）：事件的过滤参数（例如，状态、优先级）。\n * `pagination` （可选对象）：分页详细信息，如页面大小/偏移量。\n * **返回**：Datadog 事件和相关元数据的数组。\n\n2. `get_incident`\n\n * 检索有关特定 Datadog 事件的详细信息。\n * **输入**：\n * `incident_id` （字符串）：要获取详细信息的事件 ID。\n * **返回**：详细事件信息（标题、状态、时间戳等）。\n\n3. `get_monitors`\n\n * 获取 Datadog 监视器的状态。\n * **输入**：\n * `groupStates` （可选数组）：要过滤的状态（例如，警报、警告、无数据、正常）。\n * `name` （可选字符串）：按名称过滤。\n * `tags` （可选数组）：按标签过滤。\n * **返回**：监控数据及其状态摘要。\n\n4. `get_logs`\n\n * 从 Datadog 搜索并检索日志。\n * **输入**：\n * `query` （字符串）：Datadog 记录查询字符串。\n * `from` （数字）：以纪元秒为单位的开始时间。\n * `to` （数字）：以纪元秒为单位的结束时间。\n * `limit` （可选数字）：返回的最大日志数量（默认为 100）。\n * **返回**：匹配日志的数组。\n\n5. `list_dashboards`\n\n * 从 Datadog 获取仪表板列表。\n * **输入**：\n * `name` （可选字符串）：按名称过滤仪表板。\n * `tags` （可选数组）：按标签过滤仪表板。\n * **返回**：带有 URL 引用的仪表板数组。\n\n6. `get_dashboard`\n\n * 从 Datadog 检索特定的仪表板。\n * **输入**：\n * `dashboard_id` （字符串）：要获取的仪表板的 ID。\n * **返回**：仪表板详细信息，包括标题、小部件等。\n\n7. `query_metrics`\n\n * 从 Datadog 检索指标数据。\n * **输入**：\n * `query` （字符串）：指标查询字符串。\n * `from` （数字）：以纪元秒为单位的开始时间。\n * `to` （数字）：以纪元秒为单位的结束时间。\n * **返回**：查询时间范围的指标数据。\n\n8. `list_traces`\n\n * 从 Datadog 检索 APM 跟踪列表。\n * **输入**：\n * `query` （字符串）：Datadog APM 跟踪查询字符串。\n * `from` （数字）：以纪元秒为单位的开始时间。\n * `to` （数字）：以纪元秒为单位的结束时间。\n * `limit` （可选数字）：要返回的最大跟踪数（默认为 100）。\n * `sort` （可选字符串）：跟踪的排序顺序（默认为“-timestamp”）。\n * `service` （可选字符串）：按服务名称过滤。\n * `operation` （可选字符串）：按操作名称过滤。\n * **返回**：来自 Datadog APM 的匹配跟踪数组。\n\n9. `list_hosts`\n\n * 从 Datadog 获取主机列表。\n * **输入**：\n * `filter` （可选字符串）：搜索结果的过滤字符串。\n * `sort_field` （可选字符串）：用于对主机进行排序的字段。\n * `sort_dir` （可选字符串）：排序方向（升序/降序）。\n * `start` （可选数字）：分页的起始偏移量。\n * `count` （可选数字）：要返回的最大主机数（最大值：1000）。\n * `from` （可选数字）：从此 UNIX 时间戳搜索主机。\n * `include_muted_hosts_data` （可选布尔值）：包括静音主机状态和到期时间。\n * `include_hosts_metadata` （可选布尔值）：包含主机元数据（版本、平台等）。\n * **返回**：主机数组，其中包含名称、ID、别名、应用程序、静音状态等详细信息。\n\n10. `get_active_hosts_count`\n\n* 获取 Datadog 中活跃主机的总数。\n* **输入**：\n * `from` （可选数字）：您想要获取活动主机总数的秒数（默认为 2 小时）。\n* **返回**：活跃和正常运行的主机总数。\n\n11. `mute_host`\n\n* 在 Datadog 中将主机静音。\n* **输入**：\n * `hostname` （字符串）：要静音的主机的名称。\n * `message` （可选字符串）：与此主机静音相关的消息。\n * `end` （可选数字）：静音结束的 POSIX 时间戳。\n * `override` （可选布尔值）：如果为真并且主机已静音，则替换现有的结束时间。\n* **返回**：成功状态和确认消息。\n\n12. `unmute_host`\n\n* 在 Datadog 中取消主机静音。\n* **输入**：\n * `hostname` （字符串）：要取消静音的主机的名称。\n* **返回**：成功状态和确认消息。\n\n13. `list_downtimes`\n\n* 列出 Datadog 的计划停机时间。\n* **输入**：\n * `currentOnly` （可选布尔值）：为真时仅返回当前活动的停机时间。\n * `monitorId` （可选数字）：按监视器 ID 过滤。\n* **返回**：计划停机时间数组，其中包含范围、监控信息和计划等详细信息。\n\n14. `schedule_downtime`\n\n* 在 Datadog 中安排停机时间。\n* **输入**：\n * `scope` （字符串）：应用停机时间的范围（例如“host：my-host”）。\n * `start` （可选数字）：停机开始的 UNIX 时间戳。\n * `end` （可选数字）：停机结束的 UNIX 时间戳。\n * `message` （可选字符串）：包含在停机时间内的消息。\n * `timezone` （可选字符串）：停机时间的时区（例如“UTC”、“America/New\\_York”）。\n * `monitorId` （可选数字）：要静音的监视器的 ID。\n * `monitorTags` （可选数组）：用于过滤的监视器标签列表。\n * `recurrence` （可选对象）：停机时间的重复设置。\n * `type` （字符串）：重复类型（“天”、“周”、“月”、“年”）。\n * `period` （数字）：重复的频率（必须> = 1）。\n * `weekDays` （可选数组）：每周重复的星期几。\n * `until` （可选数字）：循环结束时的 UNIX 时间戳。\n* **返回**：计划停机详细信息，包括 ID 和活动状态。\n\n15. `cancel_downtime`\n\n* 取消 Datadog 中的预定停机时间。\n* **输入**：\n * `downtimeId` （数字）：要取消的停机时间的 ID。\n* **返回**：停机取消确认。\n\n16. `get_rum_applications`\n\n* 获取组织内的所有 RUM 应用程序。\n* **输入**：无。\n* **返回**：RUM 应用程序列表。\n\n17. `get_rum_events`\n\n* 从 Datadog 搜索并检索 RUM 事件。\n* **输入**：\n * `query` （字符串）：Datadog RUM 查询字符串。\n * `from` （数字）：以纪元秒为单位的开始时间。\n * `to` （数字）：以纪元秒为单位的结束时间。\n * `limit` （可选数字）：要返回的最大事件数（默认值：100）。\n* **返回**：RUM 事件数组。\n\n18. `get_rum_grouped_event_count`\n\n* 按指定维度搜索、分组和计数 RUM 事件。\n* **输入**：\n * `query` （可选字符串）：RUM 搜索的附加查询过滤器（默认值：“\\*”）。\n * `from` （数字）：以纪元秒为单位的开始时间。\n * `to` （数字）：以纪元秒为单位的结束时间。\n * `groupBy` （可选字符串）：按维度对结果进行分组（默认值：“application.name”）。\n* **返回**：分组事件计数。\n\n19. `get_rum_page_performance`\n\n* 从 RUM 数据中获取页面（视图）性能指标。\n* **输入**：\n * `query` （可选字符串）：RUM 搜索的附加查询过滤器（默认值：“\\*”）。\n * `from` （数字）：以纪元秒为单位的开始时间。\n * `to` （数字）：以纪元秒为单位的结束时间。\n * `metricNames` （字符串数组）：要检索的指标名称数组（例如，“view.load\\_time”、“view.first\\_contentful\\_paint”）。\n* **返回**：性能指标，包括每个指标的平均值、最小值、最大值和计数。\n\n20. `get_rum_page_waterfall`\n\n* 检索按应用程序名称和会话 ID 过滤的 RUM 页面（视图）瀑布数据。\n* **输入**：\n * `applicationName` （字符串）：用于过滤事件的应用程序名称。\n * `sessionId` （字符串）：用于过滤事件的会话 ID。\n* **返回**：指定应用程序和会话的瀑布数据。\n\n## 设置\n\n### Datadog 凭证\n\n您需要有效的 Datadog API 凭证才能使用此 MCP 服务器：\n\n* `DATADOG_API_KEY` ：您的 Datadog API 密钥\n* `DATADOG_APP_KEY` ：您的 Datadog 应用程序密钥\n* `DATADOG_SITE` （可选）：Datadog 网站（例如`datadoghq.eu` ）\n\n在运行服务器之前将它们导出到您的环境中：\n\n```bash\nexport DATADOG_API_KEY=\"your_api_key\"\nexport DATADOG_APP_KEY=\"your_app_key\"\nexport DATADOG_SITE=\"your_datadog_site\"\n```\n\n## 安装\n\n### 通过 Smithery 安装\n\n要通过[Smithery](https://smithery.ai/server/@winor30/mcp-server-datadog)自动为 Claude Desktop 安装 Datadog MCP 服务器：\n\n```bash\nnpx -y @smithery/cli install @winor30/mcp-server-datadog --client claude\n```\n\n### 手动安装\n\n```bash\npnpm install\npnpm build\npnpm watch # for development with auto-rebuild\n```\n\n## 与 Claude Desktop 一起使用\n\n要将其与 Claude Desktop 一起使用，请将以下内容添加到您的`claude_desktop_config.json`中：\n\n在 MacOS 上： `~/Library/Application Support/Claude/claude_desktop_config.json`\\\n在 Windows 上： `%APPDATA%/Claude/claude_desktop_config.json`\n\n```json\n{\n \"mcpServers\": {\n \"github\": {\n \"command\": \"npx\",\n \"args\": [\"-y\", \"@modelcontextprotocol/server-github\"],\n \"env\": {\n \"GITHUB_PERSONAL_ACCESS_TOKEN\": \"\"\n }\n }\n }\n}\n```\n\n```json\n{\n \"mcpServers\": {\n \"datadog\": {\n \"command\": \"/path/to/mcp-server-datadog/build/index.js\",\n \"env\": {\n \"DATADOG_API_KEY\": \"\",\n \"DATADOG_APP_KEY\": \"\",\n \"DATADOG_SITE\": \"\" // Optional\n }\n }\n }\n}\n```\n\n或者通过`npx`指定：\n\n```json\n{\n \"mcpServers\": {\n \"mcp-server-datadog\": {\n \"command\": \"npx\",\n \"args\": [\"-y\", \"@winor30/mcp-server-datadog\"],\n \"env\": {\n \"DATADOG_API_KEY\": \"\",\n \"DATADOG_APP_KEY\": \"\",\n \"DATADOG_SITE\": \"\" // Optional\n }\n }\n }\n}\n```\n\n## 调试\n\n由于 MCP 服务器通过标准输入/输出进行通信，调试有时会比较棘手。我们建议使用[MCP 检查器](https://github.com/modelcontextprotocol/inspector)。您可以使用以下命令运行检查器：\n\n```bash\nnpm run inspector\n```\n\n检查器将提供一个 URL，您可以在浏览器中打开它来查看日志并手动发送请求。\n\n## 贡献\n\n欢迎贡献代码！如果您有任何建议、错误报告或改进建议，欢迎随时提交问题或拉取请求。\n\n## 执照\n\n该项目采用[Apache 许可证 2.0 版](./LICENSE)授权。","Chinese","zh-CN","githubUser","locale",{"_69":70,"_71":72,"_13":89,"_99":32,"_100":32,"_101":102,"_105":106,"_128":-5,"_16":129,"_130":131,"_132":133,"_33":34,"_144":118,"_145":146,"_150":-5,"_151":152,"_153":-5,"_154":155,"_160":-5,"_140":34,"_161":162,"_165":166,"_119":411,"_412":413},"addedAt","2025-03-06T14:28:43.463463966Z","argumentsJsonSchema",{"_73":74,"_86":87,"_78":88},"properties",{"_75":76,"_80":81,"_83":84},"DATADOG_SITE",{"_31":77,"_78":79},"The Datadog site (e.g. datadoghq.eu)","type","string","DATADOG_API_KEY",{"_31":82,"_78":79},"Your Datadog API key","DATADOG_APP_KEY",{"_31":85,"_78":79},"Your Datadog Application 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