[{"_1":2,"_529":-5,"_530":-5},"loaderData",{"_3":4,"_22":23,"_24":25,"_365":366},"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",6162166,"membership","referenceId","0196b407-a078-74a7-8da0-b0620c13b29a","userAccount","routes/_public/_layout",{},"routes/_public/mcp/servers/~namespace/~slug/_pages/_layout",{"_26":27,"_68":-5,"_69":28,"_29":70,"_283":284,"_364":193},"availableLocales",[28,40,47,54,61],{"_29":30,"_33":37,"_38":39},"mcpServer",{"_31":32,"_33":34,"_35":36},"description","MCP-compatible server that enables AI assistants to interact with Lightdash analytics data, providing tools to list and retrieve projects, spaces, charts, dashboards, and metrics through a standardized interface.","name","Lightdash MCP Server","readme","# lightdash-mcp-server\n[![smithery badge](https://smithery.ai/badge/@syucream/lightdash-mcp-server)](https://smithery.ai/server/@syucream/lightdash-mcp-server)\n[![npm version](https://badge.fury.io/js/lightdash-mcp-server.svg)](https://badge.fury.io/js/lightdash-mcp-server)\n\nA [MCP(Model Context Protocol)](https://www.anthropic.com/news/model-context-protocol) server that accesses to [Lightdash](https://www.lightdash.com/).\n\nThis server provides MCP-compatible access to Lightdash's API, allowing AI assistants to interact with your Lightdash data through a standardized interface.\n\n\n $\"Lightdash$ \n\n\n## Features\n\nAvailable tools:\n\n- `list_projects` - List all projects in the Lightdash organization\n- `get_project` - Get details of a specific project\n- `list_spaces` - List all spaces in a project\n- `list_charts` - List all charts in a project\n- `list_dashboards` - List all dashboards in a project\n- `get_custom_metrics` - Get custom metrics for a project\n- `get_catalog` - Get catalog for a project\n- `get_metrics_catalog` - Get metrics catalog for a project\n- `get_charts_as_code` - Get charts as code for a project\n- `get_dashboards_as_code` - Get dashboards as code for a project\n\n## Quick Start\n\n### Installation\n\n#### Installing via Smithery\n\nTo install Lightdash MCP Server for Claude Desktop automatically via [Smithery](https://smithery.ai/server/@syucream/lightdash-mcp-server):\n\n```bash\nnpx -y @smithery/cli install lightdash-mcp-server --client claude\n```\n\n#### Manual Installation\n```bash\nnpm install lightdash-mcp-server\n```\n\n### Configuration\n\nCreate a `.env` file with your Lightdash API credentials:\n\n```env\nLIGHTDASH_API_KEY=your_api_key\nLIGHTDASH_API_URL=https://app.lightdash.cloud # or your custom Lightdash instance URL\n```\n\n### Usage\n\n1. Start the MCP server.\n\nDirectly:\n```bash\nnpx lightdash-mcp-server\n```\nOr, run the installed module with node.\n\n2. Edit your MCP configuration json:\n```json\n...\n \"lightdash\": {\n \"command\": \"npx\",\n \"args\": [\n \"-y\",\n \"lightdash-mcp-server\"\n ],\n \"env\": {\n \"LIGHTDASH_API_KEY\": \"\",\n \"LIGHTDASH_API_URL\": \"https://\"\n }\n },\n...\n```\n\n## Development\n\n### Available Scripts\n\n- `npm run dev` - Start the server in development mode with hot reloading\n- `npm run build` - Build the project for production\n- `npm run start` - Start the production server\n- `npm run lint` - Run linting checks (ESLint and Prettier)\n- `npm run fix` - Automatically fix linting issues\n- `npm run examples` - Run the example scripts\n\n### Contributing\n\n1. Fork the repository\n2. Create your feature branch\n3. Run tests and linting: `npm run lint`\n4. Commit your changes\n5. Push to the branch\n6. Create a Pull Request\n","English","tag","en-US",{"_29":41,"_33":45,"_38":46},{"_31":42,"_33":43,"_35":44},"Servidor compatible con MCP que permite a los asistentes de IA interactuar con los datos analíticos de Lightdash, proporcionando herramientas para enumerar y recuperar proyectos, espacios, gráficos, paneles y métricas a través de una interfaz estandarizada.","Servidor MCP de Lightdash","# servidor lightdash-mcp\n\n[![insignia de herrería](https://smithery.ai/badge/@syucream/lightdash-mcp-server)](https://smithery.ai/server/@syucream/lightdash-mcp-server)[![versión npm](https://badge.fury.io/js/lightdash-mcp-server.svg)](https://badge.fury.io/js/lightdash-mcp-server)\n\nUn servidor [MCP (Protocolo de contexto de modelo)](https://www.anthropic.com/news/model-context-protocol) que accede a [Lightdash](https://www.lightdash.com/) .\n\nEste servidor proporciona acceso compatible con MCP a la API de Lightdash, lo que permite que los asistentes de IA interactúen con sus datos de Lightdash a través de una interfaz estandarizada.\n\n## Características\n\nHerramientas disponibles:\n\n* `list_projects` - Lista todos los proyectos en la organización Lightdash\n* `get_project` - Obtener detalles de un proyecto específico\n* `list_spaces` - Lista todos los espacios en un proyecto\n* `list_charts` - Lista todos los gráficos de un proyecto\n* `list_dashboards` - Lista todos los paneles de un proyecto\n* `get_custom_metrics` - Obtener métricas personalizadas para un proyecto\n* `get_catalog` - Obtener el catálogo de un proyecto\n* `get_metrics_catalog` - Obtener el catálogo de métricas de un proyecto\n* `get_charts_as_code` - Obtener gráficos como código para un proyecto\n* `get_dashboards_as_code` - Obtener paneles como código para un proyecto\n\n## Inicio rápido\n\n### Instalación\n\n#### Instalación mediante herrería\n\nPara instalar Lightdash MCP Server para Claude Desktop automáticamente a través de [Smithery](https://smithery.ai/server/@syucream/lightdash-mcp-server) :\n\n```bash\nnpx -y @smithery/cli install lightdash-mcp-server --client claude\n```\n\n#### Instalación manual\n\n```bash\nnpm install lightdash-mcp-server\n```\n\n### Configuración\n\nCree un archivo `.env` con sus credenciales de API de Lightdash:\n\n```env\nLIGHTDASH_API_KEY=your_api_key\nLIGHTDASH_API_URL=https://app.lightdash.cloud # or your custom Lightdash instance URL\n```\n\n### Uso\n\n1. Inicie el servidor MCP.\n\nDirectamente:\n\n```bash\nnpx lightdash-mcp-server\n```\n\nO bien, ejecute el módulo instalado con el nodo.\n\n2. Edite su json de configuración de MCP:\n\n```json\n...\n \"lightdash\": {\n \"command\": \"npx\",\n \"args\": [\n \"-y\",\n \"lightdash-mcp-server\"\n ],\n \"env\": {\n \"LIGHTDASH_API_KEY\": \"\",\n \"LIGHTDASH_API_URL\": \"https://\"\n }\n },\n...\n```\n\n## Desarrollo\n\n### Scripts disponibles\n\n* `npm run dev` - Inicia el servidor en modo de desarrollo con recarga en caliente\n* `npm run build` : compila el proyecto para producción\n* `npm run start` : inicia el servidor de producción\n* `npm run lint` : ejecuta comprobaciones de linting (ESLint y Prettier)\n* `npm run fix` : corrige automáticamente los problemas de pelusa\n* `npm run examples` : ejecutar los scripts de ejemplo\n\n### Contribuyendo\n\n1. Bifurcar el repositorio\n2. Crea tu rama de funciones\n3. Ejecutar pruebas y linting: `npm run lint`\n4. Confirme sus cambios\n5. Empujar hacia la rama\n6. Crear una solicitud de extracción","Spanish","es-ES",{"_29":48,"_33":52,"_38":53},{"_31":49,"_33":50,"_35":51},"AI アシスタントが Lightdash 分析データと対話できるようにし、標準化されたインターフェースを通じてプロジェクト、スペース、チャート、ダッシュボード、メトリックを一覧表示および取得するためのツールを提供する MCP 互換サーバー。","Lightdash MCP サーバー","# lightdash-mcp-server\n\n[![鍛冶屋のバッジ](https://smithery.ai/badge/@syucream/lightdash-mcp-server)](https://smithery.ai/server/@syucream/lightdash-mcp-server)[![npmバージョン](https://badge.fury.io/js/lightdash-mcp-server.svg)](https://badge.fury.io/js/lightdash-mcp-server)\n\n[Lightdash](https://www.lightdash.com/)へアクセスする[MCP(Model Context Protocol)](https://www.anthropic.com/news/model-context-protocol)サーバー。\n\nこのサーバーは、Lightdash の API への MCP 互換アクセスを提供し、AI アシスタントが標準化されたインターフェースを通じて Lightdash データと対話できるようにします。\n\n## 特徴\n\n利用可能なツール:\n\n* `list_projects` - Lightdash組織内のすべてのプロジェクトを一覧表示します\n* `get_project` - 特定のプロジェクトの詳細を取得する\n* `list_spaces` - プロジェクト内のすべてのスペースを一覧表示する\n* `list_charts` - プロジェクト内のすべてのチャートを一覧表示する\n* `list_dashboards` - プロジェクト内のすべてのダッシュボードを一覧表示する\n* `get_custom_metrics` - プロジェクトのカスタムメトリックを取得する\n* `get_catalog` - プロジェクトのカタログを取得する\n* `get_metrics_catalog` - プロジェクトのメトリクスカタログを取得する\n* `get_charts_as_code` - プロジェクトのチャートをコードとして取得する\n* `get_dashboards_as_code` - プロジェクトのダッシュボードをコードとして取得する\n\n## クイックスタート\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/@syucream/lightdash-mcp-server)経由で Claude Desktop 用の Lightdash 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 lightdash-mcp-server --client claude\n```\n\n#### 手動インストール\n\n```bash\nnpm install lightdash-mcp-server\n```\n\n### 構成\n\nLightdash API 認証情報を使用して`.env`ファイルを作成します。\n\n```env\nLIGHTDASH_API_KEY=your_api_key\nLIGHTDASH_API_URL=https://app.lightdash.cloud # or your custom Lightdash instance URL\n```\n\n### 使用法\n\n1. MCP サーバーを起動します。\n\n直接：\n\n```bash\nnpx lightdash-mcp-server\n```\n\nまたは、インストールされたモジュールを node で実行します。\n\n2. MCP 構成 json を編集します。\n\n```json\n...\n \"lightdash\": {\n \"command\": \"npx\",\n \"args\": [\n \"-y\",\n \"lightdash-mcp-server\"\n ],\n \"env\": {\n \"LIGHTDASH_API_KEY\": \"\",\n \"LIGHTDASH_API_URL\": \"https://\"\n }\n },\n...\n```\n\n## 発達\n\n### 利用可能なスクリプト\n\n* `npm run dev` - ホットリロードで開発モードでサーバーを起動します\n* `npm run build` - 本番環境用にプロジェクトをビルドする\n* `npm run start` - 本番サーバーを起動する\n* `npm run lint` - リンティングチェックを実行する（ESLint と Prettier）\n* `npm run fix` - リンティングの問題を自動的に修正する\n* `npm run examples` - サンプルスクリプトを実行する\n\n### 貢献\n\n1. リポジトリをフォークする\n2. 機能ブランチを作成する\n3. テストとリンティングを実行する: `npm run lint`\n4. 変更をコミットする\n5. ブランチにプッシュする\n6. プルリクエストを作成する","Japanese","ja-JP",{"_29":55,"_33":59,"_38":60},{"_31":56,"_33":57,"_35":58},"AI 어시스턴트가 Lightdash 분석 데이터와 상호 작용할 수 있도록 하는 MCP 호환 서버로, 표준화된 인터페이스를 통해 프로젝트, 공간, 차트, 대시보드 및 지표를 나열하고 검색할 수 있는 도구를 제공합니다.","Lightdash MCP 서버","# lightdash-mcp-서버\n\n[![대장간 배지](https://smithery.ai/badge/@syucream/lightdash-mcp-server)](https://smithery.ai/server/@syucream/lightdash-mcp-server) [![npm 버전](https://badge.fury.io/js/lightdash-mcp-server.svg)](https://badge.fury.io/js/lightdash-mcp-server)\n\n[Lightdash](https://www.lightdash.com/) 에 접근하는 [MCP(Model Context Protocol)](https://www.anthropic.com/news/model-context-protocol) 서버입니다.\n\n이 서버는 Lightdash API에 대한 MCP 호환 액세스를 제공하여 AI 어시스턴트가 표준화된 인터페이스를 통해 Lightdash 데이터와 상호 작용할 수 있도록 합니다.\n\n## 특징\n\n사용 가능한 도구:\n\n* `list_projects` - Lightdash 조직의 모든 프로젝트를 나열합니다.\n* `get_project` - 특정 프로젝트의 세부 정보를 가져옵니다\n* `list_spaces` - 프로젝트의 모든 공간 나열\n* `list_charts` - 프로젝트의 모든 차트를 나열합니다\n* `list_dashboards` - 프로젝트의 모든 대시보드 나열\n* `get_custom_metrics` - 프로젝트에 대한 사용자 정의 메트릭 가져오기\n* `get_catalog` - 프로젝트에 대한 카탈로그 가져오기\n* `get_metrics_catalog` - 프로젝트에 대한 메트릭 카탈로그 가져오기\n* `get_charts_as_code` - 프로젝트에 대한 코드로 차트 가져오기\n* `get_dashboards_as_code` - 프로젝트의 대시보드를 코드로 가져오기\n\n## 빠른 시작\n\n### 설치\n\n#### Smithery를 통해 설치\n\n[Smithery를](https://smithery.ai/server/@syucream/lightdash-mcp-server) 통해 Claude Desktop에 Lightdash MCP 서버를 자동으로 설치하려면:\n\n지엑스피1\n\n#### 수동 설치\n\n```bash\nnpm install lightdash-mcp-server\n```\n\n### 구성\n\nLightdash API 자격 증명으로 `.env` 파일을 만듭니다.\n\n```env\nLIGHTDASH_API_KEY=your_api_key\nLIGHTDASH_API_URL=https://app.lightdash.cloud # or your custom Lightdash instance URL\n```\n\n### 용법\n\n1. MCP 서버를 시작합니다.\n\n곧장:\n\n```bash\nnpx lightdash-mcp-server\n```\n\n또는 설치된 모듈을 node로 실행합니다.\n\n2. MCP 구성 JSON을 편집하세요.\n\n```json\n...\n \"lightdash\": {\n \"command\": \"npx\",\n \"args\": [\n \"-y\",\n \"lightdash-mcp-server\"\n ],\n \"env\": {\n \"LIGHTDASH_API_KEY\": \"\",\n \"LIGHTDASH_API_URL\": \"https://\"\n }\n },\n...\n```\n\n## 개발\n\n### 사용 가능한 스크립트\n\n* `npm run dev` - 핫 리로딩을 사용하여 개발 모드로 서버 시작\n* `npm run build` - 프로덕션을 위한 프로젝트 빌드\n* `npm run start` - 프로덕션 서버 시작\n* `npm run lint` - 린팅 검사 실행(ESLint 및 Prettier)\n* `npm run fix` - 린팅 문제를 자동으로 수정합니다\n* `npm run examples` - 예제 스크립트 실행\n\n### 기여하다\n\n1. 저장소를 포크하세요\n2. 기능 브랜치를 생성하세요\n3. 테스트 및 린팅 실행: `npm run lint`\n4. 변경 사항을 커밋하세요\n5. 지점으로 밀어 넣기\n6. 풀 리퀘스트 만들기","Korean","ko-KR",{"_29":62,"_33":66,"_38":67},{"_31":63,"_33":64,"_35":65},"MCP 兼容服务器，使 AI 助手能够与 Lightdash 分析数据进行交互，提供通过标准化界面列出和检索项目、空间、图表、仪表板和指标的工具。","Lightdash MCP 服务器","# lightdash-mcp-服务器\n\n[![铁匠徽章](https://smithery.ai/badge/@syucream/lightdash-mcp-server)](https://smithery.ai/server/@syucream/lightdash-mcp-server) [![npm 版本](https://badge.fury.io/js/lightdash-mcp-server.svg)](https://badge.fury.io/js/lightdash-mcp-server)\n\n访问[Lightdash](https://www.lightdash.com/)的[MCP（模型上下文协议）](https://www.anthropic.com/news/model-context-protocol)服务器。\n\n该服务器提供与 MCP 兼容的 Lightdash API 访问，允许 AI 助手通过标准化界面与您的 Lightdash 数据进行交互。\n\n## 特征\n\n可用工具：\n\n* `list_projects` - 列出 Lightdash 组织中的所有项目\n* `get_project` - 获取特定项目的详细信息\n* `list_spaces` - 列出项目中的所有空间\n* `list_charts` - 列出项目中的所有图表\n* `list_dashboards` - 列出项目中的所有仪表板\n* `get_custom_metrics` - 获取项目的自定义指标\n* `get_catalog` - 获取项目目录\n* `get_metrics_catalog` - 获取项目的指标目录\n* `get_charts_as_code` - 获取项目图表的代码\n* `get_dashboards_as_code` - 获取项目仪表板的代码\n\n## 快速入门\n\n### 安装\n\n#### 通过 Smithery 安装\n\n要通过[Smithery](https://smithery.ai/server/@syucream/lightdash-mcp-server)自动为 Claude Desktop 安装 Lightdash MCP 服务器：\n\n```bash\nnpx -y @smithery/cli install lightdash-mcp-server --client claude\n```\n\n#### 手动安装\n\n```bash\nnpm install lightdash-mcp-server\n```\n\n### 配置\n\n使用您的 Lightdash API 凭证创建一个`.env`文件：\n\n```env\nLIGHTDASH_API_KEY=your_api_key\nLIGHTDASH_API_URL=https://app.lightdash.cloud # or your custom Lightdash instance URL\n```\n\n### 用法\n\n1. 启动 MCP 服务器。\n\n直接地：\n\n```bash\nnpx lightdash-mcp-server\n```\n\n或者，使用节点运行已安装的模块。\n\n2. 编辑您的 MCP 配置 json：\n\n```json\n...\n \"lightdash\": {\n \"command\": \"npx\",\n \"args\": [\n \"-y\",\n \"lightdash-mcp-server\"\n ],\n \"env\": {\n \"LIGHTDASH_API_KEY\": \"\",\n \"LIGHTDASH_API_URL\": \"https://\"\n }\n },\n...\n```\n\n## 发展\n\n### 可用脚本\n\n* `npm run dev` - 使用热重载以开发模式启动服务器\n* `npm run build`构建生产项目\n* `npm run start`启动生产服务器\n* `npm run lint` - 运行 linting 检查（ESLint 和 Prettier）\n* `npm run fix` - 自动修复 linting 问题\n* `npm run examples` - 运行示例脚本\n\n### 贡献\n\n1. 分叉存储库\n2. 创建你的功能分支\n3. 运行测试和 lint： `npm run lint`\n4. 提交你的更改\n5. 推送到分支\n6. 创建拉取请求","Chinese","zh-CN","githubUser","locale",{"_71":72,"_73":74,"_13":90,"_99":32,"_100":32,"_101":102,"_105":106,"_129":-5,"_16":130,"_131":132,"_133":134,"_33":34,"_165":119,"_166":167,"_170":-5,"_171":172,"_173":-5,"_174":175,"_180":-5,"_141":115,"_181":-5,"_182":183,"_120":280,"_281":282},"addedAt",["D",1741475082715],"argumentsJsonSchema",{"_75":76,"_87":88,"_80":89},"properties",{"_77":78,"_82":83},"LIGHTDASH_API_KEY",{"_31":79,"_80":81},"Your Lightdash API key","type","string","LIGHTDASH_API_URL",{"_84":85,"_31":86,"_80":81},"default","https://app.lightdash.cloud/api/v1","The URL of your Lightdash API instance","required",[77],"object",[91,92,93,94,95,96,97,98],"category:databases","category:search","environment:network","hosting:remote-capable","language:javascript","security_grade:a","quality_grade:a","license_grade:a","descriptionMarkdown","descriptionPlainText","githubProject",{"_35":36,"_103":104},"url","https://github.com/syucream/lightdash-mcp-server","githubRepository",{"_107":108,"_109":110,"_111":112,"_113":114,"_33":115,"_116":117,"_122":123,"_124":125,"_127":128},"defaultBranch","main","fullName","syucream/lightdash-mcp-server","githubTreeId",102703,"language","JavaScript","lightdash-mcp-server","owner",{"_118":119,"_120":121},"login","syucream","uid","idma3dv6vw","recentStargazers",3,"spdxLicense",{"_33":126},"MIT License","stargazers",10,"glamaJson",1210,"inspectable",true,"integrations",[135,145,152,158],{"_136":137,"_31":143,"_120":144},"brand",{"_138":139,"_33":140,"_141":142},"logoSvgPath","M24 0v24H0V0h24ZM10.933 15.89H6.84v5.52h4.198v-.93H7.955v-1.503h2.77v-.93h-2.77v-1.224h2.978v-.934Zm2.146 0h-1.084v5.52h1.035v-3.6l2.226 3.6h1.118v-5.52h-1.036v3.686l-2.259-3.687Zm5.117 0h-1.208l1.973 5.52h1.19l1.976-5.52h-1.182l-1.352 4.085-1.397-4.086ZM5.4 19.68H3.72v1.68H5.4v-1.68Z",".ENV","slug","dotenv","Used for configuration management by storing Lightdash API credentials in environment variables.","2zwjt6fod5",{"_136":146,"_31":150,"_120":151},{"_138":147,"_33":148,"_141":149},"M7.257 9.132L11.816 6.5a.369.369 0 0 1 .368 0l4.559 2.632a.369.369 0 0 1 .184.32v5.263a.37.37 0 0 1-.184.319l-4.559 2.632a.369.369 0 0 1-.368 0l-4.559-2.632a.369.369 0 0 1-.184-.32V9.452a.37.37 0 0 1 .184-.32M23.852 11.53l-5.446-9.475c-.198-.343-.564-.596-.96-.596H6.555c-.396 0-.762.253-.96.596L.149 11.509a1.127 1.127 0 0 0 0 1.117l5.447 9.398c.197.342.563.517.959.517h10.893c.395 0 .76-.17.959-.512l5.446-9.413a1.069 1.069 0 0 0 0-1.086m-4.51 4.556a.4.4 0 0 1-.204.338L12.2 20.426a.395.395 0 0 1-.392 0l-6.943-4.002a.4.4 0 0 1-.205-.338V8.08c0-.14.083-.269.204-.338L11.8 3.74c.12-.07.272-.07.392 0l6.943 4.003a.4.4 0 0 1 .206.338z","ESLint","eslint","Provides code linting functionality for development and contributing to the project.","y4iwrmabmn",{"_136":153,"_31":156,"_120":157},{"_138":154,"_33":155,"_141":155},"M1.763 0C.786 0 0 .786 0 1.763v20.474C0 23.214.786 24 1.763 24h20.474c.977 0 1.763-.786 1.763-1.763V1.763C24 .786 23.214 0 22.237 0zM5.13 5.323l13.837.019-.009 13.836h-3.464l.01-10.382h-3.456L12.04 19.17H5.113z","npm","Used for package installation, dependency management, and running scripts for the server.","kn0646nj64",{"_136":159,"_31":163,"_120":164},{"_138":160,"_33":161,"_141":162},"M8.571 23.429A.571.571 0 0 1 8 24H2.286a.571.571 0 0 1 0-1.143H8c.316 0 .571.256.571.572zM8 20.57H6.857a.571.571 0 0 0 0 1.143H8a.571.571 0 0 0 0-1.143zm-5.714 1.143H4.57a.571.571 0 0 0 0-1.143H2.286a.571.571 0 0 0 0 1.143zM8 18.286H2.286a.571.571 0 0 0 0 1.143H8a.571.571 0 0 0 0-1.143zM16 16H5.714a.571.571 0 0 0 0 1.143H16A.571.571 0 0 0 16 16zM2.286 17.143h1.143a.571.571 0 0 0 0-1.143H2.286a.571.571 0 0 0 0 1.143zm17.143-3.429H16a.571.571 0 0 0 0 1.143h3.429a.571.571 0 0 0 0-1.143zM9.143 14.857h4.571a.571.571 0 0 0 0-1.143H9.143a.571.571 0 0 0 0 1.143zm-6.857 0h4.571a.571.571 0 0 0 0-1.143H2.286a.571.571 0 0 0 0 1.143zM20.57 11.43H11.43a.571.571 0 0 0 0 1.142h9.142a.571.571 0 0 0 0-1.142zM9.714 12a.571.571 0 0 0-.571-.571H5.714a.571.571 0 0 0 0 1.142h3.429A.571.571 0 0 0 9.714 12zm-7.428.571h1.143a.571.571 0 0 0 0-1.142H2.286a.571.571 0 0 0 0 1.142zm19.428-3.428H16a.571.571 0 0 0 0 1.143h5.714a.571.571 0 0 0 0-1.143zM2.286 10.286H8a.571.571 0 0 0 0-1.143H2.286a.571.571 0 0 0 0 1.143zm13.143-2.857c0 .315.255.571.571.571h5.714a.571.571 0 0 0 0-1.143H16a.571.571 0 0 0-.571.572zm-8.572-.572a.571.571 0 0 0 0 1.143H8a.571.571 0 0 0 0-1.143H6.857zM2.286 8H4.57a.571.571 0 0 0 0-1.143H2.286a.571.571 0 0 0 0 1.143zm16.571-2.857c0 .315.256.571.572.571h1.142a.571.571 0 0 0 0-1.143H19.43a.571.571 0 0 0-.572.572zm-1.143 0a.571.571 0 0 0-.571-.572H12.57a.571.571 0 0 0 0 1.143h4.572a.571.571 0 0 0 .571-.571zm-15.428.571h8a.571.571 0 0 0 0-1.143h-8a.571.571 0 0 0 0 1.143zm5.143-2.857c0 .316.255.572.571.572h11.429a.571.571 0 0 0 0-1.143H8a.571.571 0 0 0-.571.571zm-5.143.572h3.428a.571.571 0 0 0 0-1.143H2.286a.571.571 0 0 0 0 1.143zm0-2.286H16A.571.571 0 0 0 16 0H2.286a.571.571 0 0 0 0 1.143z","Prettier","prettier","Handles code formatting to maintain consistent style across the codebase.","priysfxkrh","namespace","npmPackage",{"_33":115,"_168":169},"weeklyDownloads",419,"prompts","redditPostForeignId","1j6tk6k","resources","scores",{"_176":177,"_178":177,"_179":177},"license",100,"quality","security","simpleIcon","supportedPlatforms","tools",[184,194,202,209,216,223,230,237,244,251,258,267,275],{"_33":185,"_31":186,"_187":188},"list_projects","List all projects in the Lightdash organization","inputSchema",{"_80":89,"_189":190,"_75":191,"_192":193},"$schema","http://json-schema.org/draft-07/schema#",{},"additionalProperties",false,{"_33":195,"_31":196,"_187":197},"get_project","Get details of a specific project",{"_80":89,"_189":190,"_87":198,"_75":200,"_192":193},[199],"projectUuid",{"_199":201},{"_80":81},{"_33":203,"_31":204,"_187":205},"list_spaces","List all spaces in a project",{"_80":89,"_189":190,"_87":206,"_75":207,"_192":193},[199],{"_199":208},{"_80":81},{"_33":210,"_31":211,"_187":212},"list_charts","List all charts in a project",{"_80":89,"_189":190,"_87":213,"_75":214,"_192":193},[199],{"_199":215},{"_80":81},{"_33":217,"_31":218,"_187":219},"list_dashboards","List all dashboards in a project",{"_80":89,"_189":190,"_87":220,"_75":221,"_192":193},[199],{"_199":222},{"_80":81},{"_33":224,"_31":225,"_187":226},"get_custom_metrics","Get custom metrics for a project",{"_80":89,"_189":190,"_87":227,"_75":228,"_192":193},[199],{"_199":229},{"_80":81},{"_33":231,"_31":232,"_187":233},"get_catalog","Get catalog for a project",{"_80":89,"_189":190,"_87":234,"_75":235,"_192":193},[199],{"_199":236},{"_80":81},{"_33":238,"_31":239,"_187":240},"get_metrics_catalog","Get metrics catalog for a project",{"_80":89,"_189":190,"_87":241,"_75":242,"_192":193},[199],{"_199":243},{"_80":81},{"_33":245,"_31":246,"_187":247},"get_charts_as_code","Get charts as code for a project",{"_80":89,"_189":190,"_87":248,"_75":249,"_192":193},[199],{"_199":250},{"_80":81},{"_33":252,"_31":253,"_187":254},"get_dashboards_as_code","Get dashboards as code for a project",{"_80":89,"_189":190,"_87":255,"_75":256,"_192":193},[199],{"_199":257},{"_80":81},{"_33":259,"_31":260,"_187":261},"get_metadata","Get metadata for a specific table in the data catalog",{"_80":89,"_189":190,"_87":262,"_75":264,"_192":193},[199,263],"table",{"_263":265,"_199":266},{"_80":81},{"_80":81},{"_33":268,"_31":269,"_187":270},"get_analytics","Get analytics for a specific table in the data catalog",{"_80":89,"_189":190,"_87":271,"_75":272,"_192":193},[199,263],{"_263":273,"_199":274},{"_80":81},{"_80":81},{"_33":276,"_31":277,"_187":278},"get_user_attributes","Get organization user attributes",{"_80":89,"_189":190,"_75":279,"_192":193},{},"e1gbb6sflq","updatedAt",["D",1742774676468],"meta",[285,288,290,297,300,302,305,308,311,314,317,319,322,325,327,329,331,333,335],{"_286":287},"title","Lightdash MCP Server | Glama",{"_289":32,"_33":31},"content",{"_291":292,"_293":294,"_295":296},"href","https://glama.ai/mcp/servers/@syucream/lightdash-mcp-server","rel","canonical","tagName","link",{"_289":34,"_298":299},"property","og:title",{"_289":32,"_298":301},"og:description",{"_289":303,"_298":304},"https://glama.ai/logo.png","og:logo",{"_289":306,"_298":307},"https://glama.ai/mcp/servers/@syucream/lightdash-mcp-server/og-image","og:image",{"_289":309,"_298":310},"630","og:image:height",{"_289":312,"_298":313},"1200","og:image:width",{"_289":315,"_298":316},"website","og:type",{"_289":292,"_298":318},"og:url",{"_289":320,"_298":321},"Glama – MCP Hosting Platform","og:site_name",{"_289":323,"_33":324},"summary_large_image","twitter:card",{"_289":320,"_33":326},"twitter:title",{"_289":32,"_33":328},"twitter:description",{"_289":306,"_33":330},"twitter:image",{"_289":309,"_33":332},"twitter:image:height",{"_289":312,"_33":334},"twitter:image:width",{"_336":337},"script:ld+json",{"_338":339,"_340":341},"@context","http://schema.org","@graph",[342],{"_338":343,"_344":345,"_346":347},"https://schema.org","@type","BreadcrumbList","itemListElement",[348,355,359,362],{"_344":349,"_350":351,"_33":352,"_353":354},"ListItem","item","https://glama.ai/","Glama","position",1,{"_344":349,"_350":356,"_33":357,"_353":358},"https://glama.ai/mcp","MCP",2,{"_344":349,"_350":360,"_33":361,"_353":123},"https://glama.ai/mcp/servers","Servers",{"_344":349,"_350":292,"_33":34,"_353":363},4,"visitorIsMaintainer","routes/_public/mcp/servers/~namespace/~slug/_pages/_explorer/blob/~branch/~/_route",{"_367":368,"_372":108,"_29":373,"_283":461,"_485":486,"_487":488},"blob",{"_289":369,"_370":371},"node_modules\nnpm-debug.log\ndist\n.git\n.gitignore\n.env\n*.md\n.github ","fileName",".dockerignore","branch",{"_71":374,"_73":375,"_13":380,"_99":32,"_100":32,"_101":381,"_105":382,"_129":-5,"_16":130,"_131":132,"_133":385,"_33":34,"_165":119,"_166":394,"_170":-5,"_171":172,"_173":-5,"_174":395,"_180":-5,"_141":115,"_181":-5,"_182":396,"_120":280,"_281":460},["D",1741475082715],{"_75":376,"_87":379,"_80":89},{"_77":377,"_82":378},{"_31":79,"_80":81},{"_84":85,"_31":86,"_80":81},[77],[91,92,93,94,95,96,97,98],{"_35":36,"_103":104},{"_107":108,"_109":110,"_111":112,"_113":114,"_33":115,"_116":383,"_122":123,"_124":384,"_127":128},{"_118":119,"_120":121},{"_33":126},[386,388,390,392],{"_136":387,"_31":143,"_120":144},{"_138":139,"_33":140,"_141":142},{"_136":389,"_31":150,"_120":151},{"_138":147,"_33":148,"_141":149},{"_136":391,"_31":156,"_120":157},{"_138":154,"_33":155,"_141":155},{"_136":393,"_31":163,"_120":164},{"_138":160,"_33":161,"_141":162},{"_33":115,"_168":169},{"_176":177,"_178":177,"_179":177},[397,400,405,410,415,420,425,430,435,440,445,451,457],{"_33":185,"_31":186,"_187":398},{"_80":89,"_189":190,"_75":399,"_192":193},{},{"_33":195,"_31":196,"_187":401},{"_80":89,"_189":190,"_87":402,"_75":403,"_192":193},[199],{"_199":404},{"_80":81},{"_33":203,"_31":204,"_187":406},{"_80":89,"_189":190,"_87":407,"_75":408,"_192":193},[199],{"_199":409},{"_80":81},{"_33":210,"_31":211,"_187":411},{"_80":89,"_189":190,"_87":412,"_75":413,"_192":193},[199],{"_199":414},{"_80":81},{"_33":217,"_31":218,"_187":416},{"_80":89,"_189":190,"_87":417,"_75":418,"_192":193},[199],{"_199":419},{"_80":81},{"_33":224,"_31":225,"_187":421},{"_80":89,"_189":190,"_87":422,"_75":423,"_192":193},[199],{"_199":424},{"_80":81},{"_33":231,"_31":232,"_187":426},{"_80":89,"_189":190,"_87":427,"_75":428,"_192":193},[199],{"_199":429},{"_80":81},{"_33":238,"_31":239,"_187":431},{"_80":89,"_189":190,"_87":432,"_75":433,"_192":193},[199],{"_199":434},{"_80":81},{"_33":245,"_31":246,"_187":436},{"_80":89,"_189":190,"_87":437,"_75":438,"_192":193},[199],{"_199":439},{"_80":81},{"_33":252,"_31":253,"_187":441},{"_80":89,"_189":190,"_87":442,"_75":443,"_192":193},[199],{"_199":444},{"_80":81},{"_33":259,"_31":260,"_187":446},{"_80":89,"_189":190,"_87":447,"_75":448,"_192":193},[199,263],{"_263":449,"_199":450},{"_80":81},{"_80":81},{"_33":268,"_31":269,"_187":452},{"_80":89,"_189":190,"_87":453,"_75":454,"_192":193},[199,263],{"_263":455,"_199":456},{"_80":81},{"_80":81},{"_33":276,"_31":277,"_187":458},{"_80":89,"_189":190,"_75":459,"_192":193},{},["D",1742774676468],[462,464,466,468,470,471,472,474,475,476,477,478,479,480,481,482,483,484],{"_286":463},"MCP Server | Glama",{"_289":465,"_33":31},"Enterprise-grade security, privacy, and features like agents, MCP, prompt templates, and more.",{"_291":467,"_293":294,"_295":296},"https://glama.ai/mcp/servers/@syucream/lightdash-mcp-server/blob/main/",{"_289":469,"_298":299},"MCP Server",{"_289":465,"_298":301},{"_289":303,"_298":304},{"_289":473,"_298":307},"https://glama.ai/generated-images/og?title=MCP+Server",{"_289":309,"_298":310},{"_289":312,"_298":313},{"_289":315,"_298":316},{"_289":467,"_298":318},{"_289":320,"_298":321},{"_289":323,"_33":324},{"_289":320,"_33":326},{"_289":465,"_33":328},{"_289":473,"_33":330},{"_289":309,"_33":332},{"_289":312,"_33":334},"path","","treeMembers",[489,492,494,496,498,499,501,503,505,507,509,511,513,515,517,519,521,523,525,527],{"_485":490,"_80":491},"examples","tree",{"_485":493,"_80":491},".github",{"_485":495,"_80":491},"src",{"_485":497,"_80":367},"Dockerfile",{"_485":371,"_80":367},{"_485":500,"_80":367},".env.sample",{"_485":502,"_80":367},"eslint.config.js",{"_485":504,"_80":367},".eslintrc.json",{"_485":506,"_80":367},".gitignore",{"_485":508,"_80":367},"LICENSE",{"_485":510,"_80":367},".node-version",{"_485":512,"_80":367},"package.json",{"_485":514,"_80":367},"package-lock.json",{"_485":516,"_80":367},".prettierrc",{"_485":518,"_80":367},"README.md",{"_485":520,"_80":367},"smithery.yaml",{"_485":522,"_80":367},"tsconfig.build.json",{"_485":524,"_80":367},"tsconfig.dev.json",{"_485":526,"_80":367},"tsconfig.json",{"_485":528,"_80":367},"ts-node-loader.js","actionData","errors"]