[{"_1":2,"_338":-5,"_339":-5},"loaderData",{"_3":4,"_22":23,"_24":25,"_276":277},"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",7058884,"membership","referenceId","01971406-43e3-74e8-b880-2f000258007a","userAccount","routes/_public/_layout",{},"routes/_public/mcp/servers/~namespace/~slug/_pages/_layout",{"_26":27,"_68":-5,"_69":28,"_29":70,"_193":194,"_274":275},"availableLocales",[28,40,47,54,61],{"_29":30,"_33":37,"_38":39},"mcpServer",{"_31":32,"_33":34,"_35":36},"description","An MCP server to interact with a Tinybird Workspace from any MCP client.","name","Tinybird MCP server","readme","# Tinybird MCP server\n\n[![smithery badge](https://smithery.ai/badge/mcp-tinybird)](https://smithery.ai/server/@tinybirdco/mcp-tinybird)\n\nAn MCP server to interact with a Tinybird Workspace from any MCP client.\n\n $\"Tinybird$ \n\n## Features\n\n- Query Tinybird Data Sources using the Tinybird Query API\n- Get the result of existing Tinybird API Endpoints with HTTP requests\n- Push Datafiles\n\nIt supports both SSE and STDIO modes.\n\n## Usage examples\n\n- [Bluesky metrics](https://bsky.app/profile/alasdairb.com/post/3lbx2mq5urk22) ([Claude transcript](https://www.tinybird.co/blog-posts/claude-analyze-bluesky-data-tinybird-mcp-server))\n- [Web analytics starter kit metrics](https://github.com/tinybirdco/web-analytics-starter-kit) ([video](https://x.com/alrocar/status/1861849648882688341)]\n\n## Setup\n\n### Installation\n\n#### Using MCP package managers\n\n**Smithery**\n\nTo install Tinybird MCP for Claude Desktop automatically via [Smithery](https://smithery.ai/protocol/mcp-tinybird):\n\n```bash\nnpx @smithery/cli install @tinybirdco/mcp-tinybird --client claude\n```\n\n**mcp-get**\n\nYou can install the Tinybird MCP server using [mcp-get](https://github.com/michaellatman/mcp-get):\n\n```bash\nnpx @michaellatman/mcp-get@latest install mcp-tinybird\n```\n\n### Prerequisites\n\nMCP is still very new and evolving, we recommend following the [MCP documentation](https://modelcontextprotocol.io/quickstart#prerequisites) to get the MCP basics up and running.\n\nYou'll need:\n- [Tinybird Account & Workspace](https://www.tinybird.co/)\n- [Claude Desktop](https://claude.ai/)\n- [uv](https://docs.astral.sh/uv/getting-started/installation/)\n\n### Configuration\n\n#### 1. Configure Claude Desktop\n\nCreate the following file depending on your OS:\n\nOn MacOS: `~/Library/Application Support/Claude/claude_desktop_config.json`\n\nOn Windows: `%APPDATA%/Claude/claude_desktop_config.json`\n\nPaste this template in the file and replace `` and `` with your Tinybird API URL and Admin Token:\n\n```json\n{\n \"mcpServers\": {\n \"mcp-tinybird\": {\n \"command\": \"uvx\",\n \"args\": [\n \"mcp-tinybird\",\n \"stdio\"\n ],\n \"env\": {\n \"TB_API_URL\": \"\",\n \"TB_ADMIN_TOKEN\": \"\"\n }\n }\n }\n}\n```\n\n#### 2. Restart Claude Desktop\n\n\n#### SSE mode\n\nAlternatively, you can run the MCP server in SSE mode by running the following command:\n\n```bash\nuvx mcp-tinybird sse\n```\n\nThis mode is useful to integrate with an MCP client that supports SSE (like a web app).\n\n## Prompts\n\nThe server provides a single prompt:\n- [tinybird-default](https://github.com/tinybirdco/mcp-tinybird/blob/93dd9e1d3c0e33f408fe88297151a44c1dfc049c/src/mcp-tinybird/server.py#L20): Assumes you have loaded some data in Tinybird and want help exploring it.\n - Requires a \"topic\" argument which defines the topic of the data you want to explore, for example, \"Bluesky data\" or \"retail sales\".\n\nYou can configure additional prompt workflows:\n - Create a prompts Data Source in your workspace with this schema and append your prompts. The MCP loads `prompts` on initialization so you can configure it to your needs:\n```bash\nSCHEMA >\n `name` String `json:$.name`,\n `description` String `json:$.description`,\n `timestamp` DateTime `json:$.timestamp`,\n `arguments` Array(String) `json:$.arguments[:]`,\n `prompt` String `json:$.prompt`\n```\n\n## Tools\n\nThe server implements several tools to interact with the Tinybird Workspace:\n- `list-data-sources`: Lists all Data Sources in the Tinybird Workspace\n- `list-pipes`: Lists all Pipe Endpoints in the Tinybird Workspace\n- `get-data-source`: Gets the information of a Data Source given its name, including the schema.\n- `get-pipe`: Gets the information of a Pipe Endpoint given its name, including its nodes and SQL transformation to understand what insights it provides.\n- `request-pipe-data`: Requests data from a Pipe Endpoints via an HTTP request. Pipe endpoints can have parameters to filter the analytical data.\n- `run-select-query`: Allows to run a select query over a Data Source to extract insights.\n- `append-insight`: Adds a new business insight to the memo resource\n- `llms-tinybird-docs`: Contains the whole Tinybird product documentation, so you can use it to get context about what Tinybird is, what it does, API reference and more.\n- `save-event`: This allows to send an event to a Tinybird Data Source. Use it to save a user generated prompt to the prompts Data Source. The MCP server feeds from the prompts Data Source on initialization so the user can instruct the LLM the workflow to follow.\n- `analyze-pipe`: Uses the Tinybird analyze API to run a ClickHouse explain on the Pipe Endpoint query and check if indexes, sorting key, and partition key are being used and propose optimizations suggestions\n- `push-datafile`: Creates a remote Data Source or Pipe in the Tinybird Workspace from a local datafile. Use the [Filesystem MCP](https://github.com/modelcontextprotocol/servers/tree/main/src/filesystem) to save files generated by this MCP server.\n\n\n## Development\n\n### Config\nIf you are working locally add two environment variables to a `.env` file in the root of the repository:\n\n```sh\nTB_API_URL=\nTB_ADMIN_TOKEN=\n```\n\nFor local development, update your Claude Desktop configuration:\n\n```json\n{\n \"mcpServers\": {\n \"mcp-tinybird_local\": {\n \"command\": \"uv\",\n \"args\": [\n \"--directory\",\n \"/path/to/your/mcp-tinybird\",\n \"run\",\n \"mcp-tinybird\",\n \"stdio\"\n ]\n }\n }\n}\n```\n\n

Published Servers Configuration

\n\n ```json\n \"mcpServers\": {\n \"mcp-tinybird\": {\n \"command\": \"uvx\",\n \"args\": [\n \"mcp-tinybird\"\n ]\n }\n }\n ```\n

\n\n### Building and Publishing\n\nTo prepare the package for distribution:\n\n1. Sync dependencies and update lockfile:\n```bash\nuv sync\n```\n\n2. Build package distributions:\n```bash\nuv build\n```\n\nThis will create source and wheel distributions in the `dist/` directory.\n\n3. Publish to PyPI:\n```bash\nuv publish\n```\n\nNote: You'll need to set PyPI credentials via environment variables or command flags:\n- Token: `--token` or `UV_PUBLISH_TOKEN`\n- Or username/password: `--username`/`UV_PUBLISH_USERNAME` and `--password`/`UV_PUBLISH_PASSWORD`\n\n### Debugging\n\nSince MCP servers run over stdio, debugging can be challenging. For the best debugging\nexperience, we strongly recommend using the [MCP Inspector](https://github.com/modelcontextprotocol/inspector).\n\n\nYou can launch the MCP Inspector via [`npm`](https://docs.npmjs.com/downloading-and-installing-node-js-and-npm) with this command:\n\n```bash\nnpx @modelcontextprotocol/inspector uv --directory /Users/alrocar/gr/mcp-tinybird run mcp-tinybird\n```\n\nUpon launching, the Inspector will display a URL that you can access in your browser to begin debugging.\n\n### Monitoring\n\nTo monitor the MCP server, you can use any compatible Prometheus client such as [Grafana](https://grafana.com/). Learn how to monitor your MCP server [here](./mcp-analytics/README.md).\n\n","English","tag","en-US",{"_29":41,"_33":45,"_38":46},{"_31":42,"_33":43,"_35":44},"Un servidor MCP para interactuar con un espacio de trabajo Tinybird desde cualquier cliente MCP.","Servidor MCP de Tinybird","# Servidor MCP de Tinybird\n\n[![insignia de herrería](https://smithery.ai/badge/mcp-tinybird)](https://smithery.ai/server/@tinybirdco/mcp-tinybird)\n\nUn servidor MCP para interactuar con un espacio de trabajo Tinybird desde cualquier cliente MCP.\n\n## Características\n\n* Consultar fuentes de datos de Tinybird mediante la API de consulta de Tinybird\n* Obtenga el resultado de los puntos finales de la API de Tinybird existentes con solicitudes HTTP\n* Archivos de datos push\n\nAdmite los modos SSE y STDIO.\n\n## Ejemplos de uso\n\n* [Métricas de Bluesky](https://bsky.app/profile/alasdairb.com/post/3lbx2mq5urk22) ( [transcripción de Claude](https://www.tinybird.co/blog-posts/claude-analyze-bluesky-data-tinybird-mcp-server) )\n* [Métricas del kit de inicio de analítica web](https://github.com/tinybirdco/web-analytics-starter-kit) ( [vídeo](https://x.com/alrocar/status/1861849648882688341) )\n\n## Configuración\n\n### Instalación\n\n#### Uso de administradores de paquetes MCP\n\n**Herrería**\n\nPara instalar Tinybird MCP para Claude Desktop automáticamente a través de [Smithery](https://smithery.ai/protocol/mcp-tinybird) :\n\n```bash\nnpx @smithery/cli install @tinybirdco/mcp-tinybird --client claude\n```\n\n**mcp-get**\n\nPuede instalar el servidor Tinybird MCP usando [mcp-get](https://github.com/michaellatman/mcp-get) :\n\n```bash\nnpx @michaellatman/mcp-get@latest install mcp-tinybird\n```\n\n### Prerrequisitos\n\nMCP todavía es muy nuevo y está en constante evolución; recomendamos seguir la [documentación de MCP](https://modelcontextprotocol.io/quickstart#prerequisites) para poner en funcionamiento los conceptos básicos de MCP.\n\nNecesitarás:\n\n* [Cuenta y espacio de trabajo de Tinybird](https://www.tinybird.co/)\n* [Escritorio de Claude](https://claude.ai/)\n* [ultravioleta](https://docs.astral.sh/uv/getting-started/installation/)\n\n### Configuración\n\n#### 1. Configurar Claude Desktop\n\nCrea el siguiente archivo dependiendo de tu sistema operativo:\n\nEn MacOS: `~/Library/Application Support/Claude/claude_desktop_config.json`\n\nEn Windows: `%APPDATA%/Claude/claude_desktop_config.json`\n\nPegue esta plantilla en el archivo y reemplace `` y `` con la URL de API de Tinybird y el token de administrador:\n\n```json\n{\n \"mcpServers\": {\n \"mcp-tinybird\": {\n \"command\": \"uvx\",\n \"args\": [\n \"mcp-tinybird\",\n \"stdio\"\n ],\n \"env\": {\n \"TB_API_URL\": \"\",\n \"TB_ADMIN_TOKEN\": \"\"\n }\n }\n }\n}\n```\n\n#### 2. Reinicie Claude Desktop\n\n#### Modo SSE\n\nAlternativamente, puede ejecutar el servidor MCP en modo SSE ejecutando el siguiente comando:\n\n```bash\nuvx mcp-tinybird sse\n```\n\nEste modo es útil para integrarse con un cliente MCP que admita SSE (como una aplicación web).\n\n## Indicaciones\n\nEl servidor proporciona un único mensaje:\n\n* [tinybird-default](https://github.com/tinybirdco/mcp-tinybird/blob/93dd9e1d3c0e33f408fe88297151a44c1dfc049c/src/mcp-tinybird/server.py#L20) : supone que ha cargado algunos datos en Tinybird y desea ayuda para explorarlos.\n * Requiere un argumento \"tema\" que define el tema de los datos que desea explorar, por ejemplo, \"datos de Bluesky\" o \"ventas minoristas\".\n\nPuede configurar flujos de trabajo de aviso adicionales:\n\n* Cree una fuente de datos de indicaciones en su espacio de trabajo con este esquema y añada sus indicaciones. El MCP carga `prompts` al inicializarse para que pueda configurarlo según sus necesidades:\n\n```bash\nSCHEMA >\n `name` String `json:$.name`,\n `description` String `json:$.description`,\n `timestamp` DateTime `json:$.timestamp`,\n `arguments` Array(String) `json:$.arguments[:]`,\n `prompt` String `json:$.prompt`\n```\n\n## Herramientas\n\nEl servidor implementa varias herramientas para interactuar con el espacio de trabajo de Tinybird:\n\n* `list-data-sources` : enumera todas las fuentes de datos en el espacio de trabajo de Tinybird\n* `list-pipes` : enumera todos los puntos finales de tubería en el espacio de trabajo de Tinybird\n* `get-data-source` : obtiene la información de una fuente de datos dado su nombre, incluido el esquema.\n* `get-pipe` : obtiene la información de un punto final de tubería dado su nombre, incluidos sus nodos y la transformación SQL para comprender qué información proporciona.\n* `request-pipe-data` : Solicita datos de los puntos finales de una tubería mediante una solicitud HTTP. Los puntos finales de la tubería pueden tener parámetros para filtrar los datos analíticos.\n* `run-select-query` : permite ejecutar una consulta de selección sobre una fuente de datos para extraer información.\n* `append-insight` : agrega una nueva perspectiva empresarial al recurso de nota\n* `llms-tinybird-docs` : contiene toda la documentación del producto Tinybird, por lo que puede usarla para obtener contexto sobre qué es Tinybird, qué hace, referencia de API y más.\n* `save-event` : Permite enviar un evento a una fuente de datos de Tinybird. Úselo para guardar un mensaje generado por el usuario en dicha fuente. El servidor MCP se alimenta de la fuente de datos durante la inicialización para que el usuario pueda indicar al LLM el flujo de trabajo a seguir.\n* `analyze-pipe` : utiliza la API de análisis de Tinybird para ejecutar una explicación de ClickHouse en la consulta del punto final de la tubería y verificar si se están utilizando los índices, la clave de clasificación y la clave de partición y proponer sugerencias de optimizaciones.\n* `push-datafile` : Crea una fuente de datos o canalización remota en el espacio de trabajo de Tinybird a partir de un archivo de datos local. Utiliza el [MCP del sistema de archivos](https://github.com/modelcontextprotocol/servers/tree/main/src/filesystem) para guardar los archivos generados por este servidor MCP.\n\n## Desarrollo\n\n### Configuración\n\nSi está trabajando localmente, agregue dos variables de entorno a un archivo `.env` en la raíz del repositorio:\n\n```sh\nTB_API_URL=\nTB_ADMIN_TOKEN=\n```\n\nPara el desarrollo local, actualice la configuración de Claude Desktop:\n\n```json\n{\n \"mcpServers\": {\n \"mcp-tinybird_local\": {\n \"command\": \"uv\",\n \"args\": [\n \"--directory\",\n \"/path/to/your/mcp-tinybird\",\n \"run\",\n \"mcp-tinybird\",\n \"stdio\"\n ]\n }\n }\n}\n```\n\n```json\n\"mcpServers\": {\n \"mcp-tinybird\": {\n \"command\": \"uvx\",\n \"args\": [\n \"mcp-tinybird\"\n ]\n }\n}\n```\n\n### Construcción y publicación\n\nPara preparar el paquete para su distribución:\n\n1. Sincronizar dependencias y actualizar el archivo de bloqueo:\n\n```bash\nuv sync\n```\n\n2. Distribuciones de paquetes de compilación:\n\n```bash\nuv build\n```\n\nEsto creará distribuciones de origen y de rueda en el directorio `dist/` .\n\n3. Publicar en PyPI:\n\n```bash\nuv publish\n```\n\nNota: Deberás configurar las credenciales de PyPI a través de variables de entorno o indicadores de comando:\n\n* Token: `--token` o `UV_PUBLISH_TOKEN`\n* O nombre de usuario/contraseña: `--username` / `UV_PUBLISH_USERNAME` y `--password` / `UV_PUBLISH_PASSWORD`\n\n### Depuración\n\nDado que los servidores MCP se ejecutan en stdio, la depuración puede ser complicada. Para una experiencia óptima, recomendamos usar el [Inspector MCP](https://github.com/modelcontextprotocol/inspector) .\n\nPuede iniciar el Inspector MCP a través de [`npm`](https://docs.npmjs.com/downloading-and-installing-node-js-and-npm) con este comando:\n\n```bash\nnpx @modelcontextprotocol/inspector uv --directory /Users/alrocar/gr/mcp-tinybird run mcp-tinybird\n```\n\nAl iniciarse, el Inspector mostrará una URL a la que podrá acceder en su navegador para comenzar a depurar.\n\n### Escucha\n\nPara supervisar el servidor MCP, puede usar cualquier cliente Prometheus compatible, como [Grafana](https://grafana.com/) . Aprenda a supervisar su servidor MCP [aquí](./mcp-analytics/README.md) .","Spanish","es-ES",{"_29":48,"_33":52,"_38":53},{"_31":49,"_33":50,"_35":51},"任意の MCP クライアントから Tinybird Workspace と対話するための MCP サーバー。","Tinybird MCP サーバー","# Tinybird MCP サーバー\n\n[![鍛冶屋のバッジ](https://smithery.ai/badge/mcp-tinybird)](https://smithery.ai/server/@tinybirdco/mcp-tinybird)\n\n任意の MCP クライアントから Tinybird Workspace と対話するための MCP サーバー。\n\n## 特徴\n\n* Tinybird クエリ API を使用して Tinybird データソースをクエリする\n* HTTPリクエストで既存のTinybird APIエンドポイントの結果を取得する\n* データファイルのプッシュ\n\nSSE モードと STDIO モードの両方をサポートします。\n\n## 使用例\n\n* [ブルースカイメトリクス](https://bsky.app/profile/alasdairb.com/post/3lbx2mq5urk22)（[クロードのトランスクリプト](https://www.tinybird.co/blog-posts/claude-analyze-bluesky-data-tinybird-mcp-server)）\n* [ウェブ解析スターターキットのメトリクス](https://github.com/tinybirdco/web-analytics-starter-kit)（[ビデオ](https://x.com/alrocar/status/1861849648882688341)）\n\n## 設定\n\n### インストール\n\n#### MCP パッケージマネージャーの使用\n\n**鍛冶屋**\n\n[Smithery](https://smithery.ai/protocol/mcp-tinybird)経由で Claude Desktop 用の Tinybird MCP を自動的にインストールするには:\n\n```bash\nnpx @smithery/cli install @tinybirdco/mcp-tinybird --client claude\n```\n\n**mcp-get**\n\n[mcp-get](https://github.com/michaellatman/mcp-get)を使用して Tinybird MCP サーバーをインストールできます。\n\n```bash\nnpx @michaellatman/mcp-get@latest install mcp-tinybird\n```\n\n### 前提条件\n\nMCP はまだ非常に新しく、進化を続けています。MCP の基本を理解して実行するには、 [MCP ドキュメント](https://modelcontextprotocol.io/quickstart#prerequisites)に従うことをお勧めします。\n\n必要なもの:\n\n* [Tinybirdアカウントとワークスペース](https://www.tinybird.co/)\n* [クロードデスクトップ](https://claude.ai/)\n* [紫外線](https://docs.astral.sh/uv/getting-started/installation/)\n\n### 構成\n\n#### 1. Claudeデスクトップを設定する\n\nOSに応じて次のファイルを作成します。\n\nMacOSの場合: `~/Library/Application Support/Claude/claude_desktop_config.json`\n\nWindows の場合: `%APPDATA%/Claude/claude_desktop_config.json`\n\nこのテンプレートをファイルに貼り付け、 ``と``を Tinybird API URL と管理者トークンに置き換えます。\n\n```json\n{\n \"mcpServers\": {\n \"mcp-tinybird\": {\n \"command\": \"uvx\",\n \"args\": [\n \"mcp-tinybird\",\n \"stdio\"\n ],\n \"env\": {\n \"TB_API_URL\": \"\",\n \"TB_ADMIN_TOKEN\": \"\"\n }\n }\n }\n}\n```\n\n#### 2. Claude Desktopを再起動します\n\n#### SSEモード\n\nあるいは、次のコマンドを実行して、MCP サーバーを SSE モードで実行することもできます。\n\n```bash\nuvx mcp-tinybird sse\n```\n\nこのモードは、SSE をサポートする MCP クライアント (Web アプリなど) と統合する場合に便利です。\n\n## プロンプト\n\nサーバーは単一のプロンプトを提供します:\n\n* [tinybird-default](https://github.com/tinybirdco/mcp-tinybird/blob/93dd9e1d3c0e33f408fe88297151a44c1dfc049c/src/mcp-tinybird/server.py#L20) : Tinybird にいくつかのデータがロードされており、それを探索するためのヘルプが必要であると想定します。\n * 探索するデータのトピックを定義する「topic」引数が必要です (例: 「Bluesky データ」または「小売売上」)。\n\n追加のプロンプトワークフローを構成できます。\n\n* このスキーマを使用してワークスペースにプロンプトデータソースを作成し、プロンプトを追加します。MCPは初期化時に`prompts`を読み込むので、必要に応じて設定できます。\n\n```bash\nSCHEMA >\n `name` String `json:$.name`,\n `description` String `json:$.description`,\n `timestamp` DateTime `json:$.timestamp`,\n `arguments` Array(String) `json:$.arguments[:]`,\n `prompt` String `json:$.prompt`\n```\n\n## ツール\n\nサーバーは、Tinybird Workspace と対話するためのいくつかのツールを実装しています。\n\n* `list-data-sources` : Tinybird ワークスペース内のすべてのデータソースを一覧表示します\n* `list-pipes` : Tinybird ワークスペース内のすべてのパイプエンドポイントを一覧表示します。\n* `get-data-source` : 指定された名前のデータソースの情報 (スキーマを含む) を取得します。\n* `get-pipe` : 指定された名前のパイプエンドポイントの情報 (ノードや SQL 変換など) を取得し、提供される洞察を理解します。\n* `request-pipe-data` : HTTPリクエストを介してパイプエンドポイントからデータを要求します。パイプエンドポイントには、分析データをフィルタリングするためのパラメータを設定できます。\n* `run-select-query` : データソースに対して選択クエリを実行して分析情報を抽出できます。\n* `append-insight` : メモリソースに新しいビジネスインサイトを追加します\n* `llms-tinybird-docs` : Tinybird 製品のドキュメント全体が含まれているため、Tinybird の概要、機能、API リファレンスなどについてのコンテキストを取得するために使用できます。\n* `save-event` : Tinybirdデータソースにイベントを送信できます。ユーザーが生成したプロンプトをpromptsデータソースに保存するために使用します。MCPサーバーは初期化時にpromptsデータソースからフィードを受け取るため、ユーザーはLLMにワークフローを指示できます。\n* `analyze-pipe` : Tinybird analyze API を使用して、パイプエンドポイントクエリで ClickHouse explain を実行し、インデックス、ソートキー、パーティションキーが使用されているかどうかを確認し、最適化の提案を行います。\n* `push-datafile` : ローカルデータファイルからTinybirdワークスペースにリモートデータソースまたはパイプを作成します。このMCPサーバーによって生成されたファイルを保存するには、[ファイルシステムMCP](https://github.com/modelcontextprotocol/servers/tree/main/src/filesystem)を使用します。\n\n## 発達\n\n### 設定\n\nローカルで作業している場合は、リポジトリのルートにある`.env`ファイルに 2 つの環境変数を追加します。\n\n```sh\nTB_API_URL=\nTB_ADMIN_TOKEN=\n```\n\nローカル開発の場合は、Claude Desktop の構成を更新します。\n\n```json\n{\n \"mcpServers\": {\n \"mcp-tinybird_local\": {\n \"command\": \"uv\",\n \"args\": [\n \"--directory\",\n \"/path/to/your/mcp-tinybird\",\n \"run\",\n \"mcp-tinybird\",\n \"stdio\"\n ]\n }\n }\n}\n```\n\n```json\n\"mcpServers\": {\n \"mcp-tinybird\": {\n \"command\": \"uvx\",\n \"args\": [\n \"mcp-tinybird\"\n ]\n }\n}\n```\n\n### 建築と出版\n\n配布用のパッケージを準備するには:\n\n1. 依存関係を同期し、ロックファイルを更新します。\n\n```bash\nuv sync\n```\n\n2. パッケージディストリビューションをビルドします。\n\n```bash\nuv build\n```\n\nこれにより、 `dist/`ディレクトリにソースとホイールのディストリビューションが作成されます。\n\n3. PyPI に公開:\n\n```bash\nuv publish\n```\n\n注: 環境変数またはコマンドフラグを使用して PyPI 資格情報を設定する必要があります。\n\n* トークン: `--token`または`UV_PUBLISH_TOKEN`\n* またはユーザー名/パスワード: `--username` / `UV_PUBLISH_USERNAME`および`--password` / `UV_PUBLISH_PASSWORD`\n\n### デバッグ\n\nMCPサーバーはstdio経由で実行されるため、デバッグが困難になる場合があります。最適なデバッグ環境を実現するには、 [MCP Inspectorの](https://github.com/modelcontextprotocol/inspector)使用を強くお勧めします。\n\n次のコマンドを使用して、 [`npm`](https://docs.npmjs.com/downloading-and-installing-node-js-and-npm)経由で MCP Inspector を起動できます。\n\n```bash\nnpx @modelcontextprotocol/inspector uv --directory /Users/alrocar/gr/mcp-tinybird run mcp-tinybird\n```\n\n起動すると、ブラウザでアクセスしてデバッグを開始できる URL がインスペクタに表示されます。\n\n### 監視\n\nMCPサーバーを監視するには、 [Grafana](https://grafana.com/)などの互換性のあるPrometheusクライアントを使用できます。MCPサーバーの監視方法については、[こちらを](./mcp-analytics/README.md)ご覧ください。","Japanese","ja-JP",{"_29":55,"_33":59,"_38":60},{"_31":56,"_33":57,"_35":58},"모든 MCP 클라이언트에서 Tinybird Workspace와 상호 작용할 수 있는 MCP 서버입니다.","Tinybird MCP 서버","# Tinybird MCP 서버\n\n[![대장간 배지](https://smithery.ai/badge/mcp-tinybird)](https://smithery.ai/server/@tinybirdco/mcp-tinybird)\n\n모든 MCP 클라이언트에서 Tinybird Workspace와 상호 작용할 수 있는 MCP 서버입니다.\n\n## 특징\n\n* Tinybird 쿼리 API를 사용하여 Tinybird 데이터 소스 쿼리\n* HTTP 요청을 통해 기존 Tinybird API 엔드포인트의 결과를 가져옵니다.\n* 푸시 데이터 파일\n\nSSE와 STDIO 모드를 모두 지원합니다.\n\n## 사용 예\n\n* [블루스카이 메트릭스](https://bsky.app/profile/alasdairb.com/post/3lbx2mq5urk22) ( [클로드 대본](https://www.tinybird.co/blog-posts/claude-analyze-bluesky-data-tinybird-mcp-server) )\n* [웹 분석 스타터 키트 지표](https://github.com/tinybirdco/web-analytics-starter-kit) ( [비디오](https://x.com/alrocar/status/1861849648882688341) )\n\n## 설정\n\n### 설치\n\n#### MCP 패키지 관리자 사용\n\n**대장간**\n\n[Smithery](https://smithery.ai/protocol/mcp-tinybird) 를 통해 Claude Desktop에 Tinybird MCP를 자동으로 설치하는 방법:\n\n지엑스피1\n\n**mcp-get**\n\n[mcp-get을](https://github.com/michaellatman/mcp-get) 사용하여 Tinybird MCP 서버를 설치할 수 있습니다.\n\n```bash\nnpx @michaellatman/mcp-get@latest install mcp-tinybird\n```\n\n### 필수 조건\n\nMCP는 아직 매우 새롭고 계속 발전하고 있으므로 MCP 기본 사항을 익히고 실행하려면 [MCP 설명서를](https://modelcontextprotocol.io/quickstart#prerequisites) 따르는 것이 좋습니다.\n\n필요한 것:\n\n* [Tinybird 계정 및 작업 공간](https://www.tinybird.co/)\n* [클로드 데스크탑](https://claude.ai/)\n* [자외선](https://docs.astral.sh/uv/getting-started/installation/)\n\n### 구성\n\n#### 1. Claude Desktop 구성\n\nOS에 따라 다음 파일을 만듭니다.\n\nMacOS의 경우: `~/Library/Application Support/Claude/claude_desktop_config.json`\n\nWindows의 경우: `%APPDATA%/Claude/claude_desktop_config.json`\n\n이 템플릿을 파일에 붙여넣고 `` 과 `` Tinybird API URL과 관리자 토큰으로 바꾸세요.\n\n```json\n{\n \"mcpServers\": {\n \"mcp-tinybird\": {\n \"command\": \"uvx\",\n \"args\": [\n \"mcp-tinybird\",\n \"stdio\"\n ],\n \"env\": {\n \"TB_API_URL\": \"\",\n \"TB_ADMIN_TOKEN\": \"\"\n }\n }\n }\n}\n```\n\n#### 2. Claude Desktop을 다시 시작하세요\n\n#### SSE 모드\n\n또는 다음 명령을 실행하여 SSE 모드에서 MCP 서버를 실행할 수 있습니다.\n\n```bash\nuvx mcp-tinybird sse\n```\n\n이 모드는 SSE를 지원하는 MCP 클라이언트(웹 앱 등)와 통합하는 데 유용합니다.\n\n## 프롬프트\n\n서버는 단일 프롬프트를 제공합니다.\n\n* [tinybird-default](https://github.com/tinybirdco/mcp-tinybird/blob/93dd9e1d3c0e33f408fe88297151a44c1dfc049c/src/mcp-tinybird/server.py#L20) : Tinybird에 일부 데이터를 로드했고 이를 탐색하는 데 도움이 필요하다고 가정합니다.\n * 탐색하려는 데이터의 주제를 정의하는 \"주제\" 인수가 필요합니다(예: \"Bluesky 데이터\" 또는 \"소매 판매\").\n\n추가 프롬프트 워크플로를 구성할 수 있습니다.\n\n* 이 스키마를 사용하여 작업 공간에 프롬프트 데이터 소스를 생성하고 프롬프트를 추가하세요. MCP는 초기화 시 `prompts` 로드하므로 필요에 따라 구성할 수 있습니다.\n\n```bash\nSCHEMA >\n `name` String `json:$.name`,\n `description` String `json:$.description`,\n `timestamp` DateTime `json:$.timestamp`,\n `arguments` Array(String) `json:$.arguments[:]`,\n `prompt` String `json:$.prompt`\n```\n\n## 도구\n\n서버는 Tinybird Workspace와 상호 작용하기 위해 여러 도구를 구현합니다.\n\n* `list-data-sources` : Tinybird Workspace의 모든 데이터 소스를 나열합니다.\n* `list-pipes` : Tinybird 작업 공간의 모든 파이프 엔드포인트를 나열합니다.\n* `get-data-source` : 스키마를 포함하여 이름이 주어진 데이터 소스의 정보를 가져옵니다.\n* `get-pipe` : 이름이 주어진 파이프 엔드포인트의 정보, 노드, SQL 변환을 가져와서 어떤 통찰력을 제공하는지 파악합니다.\n* `request-pipe-data` : HTTP 요청을 통해 파이프 엔드포인트에 데이터를 요청합니다. 파이프 엔드포인트는 분석 데이터를 필터링하는 매개변수를 가질 수 있습니다.\n* `run-select-query` : 데이터 소스에 대한 선택 쿼리를 실행하여 통찰력을 추출할 수 있습니다.\n* `append-insight` : 메모 리소스에 새로운 비즈니스 통찰력을 추가합니다.\n* `llms-tinybird-docs` : Tinybird 제품 설명서 전체가 포함되어 있으므로, 이를 통해 Tinybird가 무엇인지, 무엇을 하는지, API 참조 등에 대한 맥락을 얻을 수 있습니다.\n* `save-event` : Tinybird 데이터 소스로 이벤트를 전송할 수 있습니다. 사용자가 생성한 프롬프트를 프롬프트 데이터 소스에 저장하는 데 사용합니다. MCP 서버는 초기화 시 프롬프트 데이터 소스에서 데이터를 제공하므로 사용자는 LLM에 따라야 할 워크플로를 지시할 수 있습니다.\n* `analyze-pipe` : Tinybird 분석 API를 사용하여 Pipe Endpoint 쿼리에 대한 ClickHouse 설명을 실행하고 인덱스, 정렬 키 및 파티션 키가 사용되고 있는지 확인하고 최적화 제안을 제안합니다.\n* `push-datafile` : 로컬 데이터 파일을 사용하여 Tinybird Workspace에 원격 데이터 소스 또는 파이프를 생성합니다. [파일 시스템 MCP를](https://github.com/modelcontextprotocol/servers/tree/main/src/filesystem) 사용하여 이 MCP 서버에서 생성된 파일을 저장합니다.\n\n## 개발\n\n### 구성\n\n로컬로 작업하는 경우 저장소 루트에 있는 `.env` 파일에 두 개의 환경 변수를 추가합니다.\n\n```sh\nTB_API_URL=\nTB_ADMIN_TOKEN=\n```\n\n로컬 개발을 위해 Claude Desktop 구성을 업데이트하세요.\n\n```json\n{\n \"mcpServers\": {\n \"mcp-tinybird_local\": {\n \"command\": \"uv\",\n \"args\": [\n \"--directory\",\n \"/path/to/your/mcp-tinybird\",\n \"run\",\n \"mcp-tinybird\",\n \"stdio\"\n ]\n }\n }\n}\n```\n\n```json\n\"mcpServers\": {\n \"mcp-tinybird\": {\n \"command\": \"uvx\",\n \"args\": [\n \"mcp-tinybird\"\n ]\n }\n}\n```\n\n### 건축 및 출판\n\n배포를 위해 패키지를 준비하려면:\n\n1. 종속성 동기화 및 잠금 파일 업데이트:\n\n```bash\nuv sync\n```\n\n2. 패키지 배포 빌드:\n\n```bash\nuv build\n```\n\n이렇게 하면 `dist/` 디렉토리에 소스와 휠 배포판이 생성됩니다.\n\n3. PyPI에 게시:\n\n```bash\nuv publish\n```\n\n참고: 환경 변수나 명령 플래그를 통해 PyPI 자격 증명을 설정해야 합니다.\n\n* 토큰: `--token` 또는 `UV_PUBLISH_TOKEN`\n* 또는 사용자 이름/비밀번호: `--username` / `UV_PUBLISH_USERNAME` 및 `--password` / `UV_PUBLISH_PASSWORD`\n\n### 디버깅\n\nMCP 서버는 stdio를 통해 실행되므로 디버깅이 어려울 수 있습니다. 최상의 디버깅 환경을 위해서는 [MCP Inspector](https://github.com/modelcontextprotocol/inspector) 사용을 강력히 권장합니다.\n\n다음 명령을 사용하여 [`npm`](https://docs.npmjs.com/downloading-and-installing-node-js-and-npm) 통해 MCP Inspector를 시작할 수 있습니다.\n\n```bash\nnpx @modelcontextprotocol/inspector uv --directory /Users/alrocar/gr/mcp-tinybird run mcp-tinybird\n```\n\nInspector를 실행하면 브라우저에서 접근하여 디버깅을 시작할 수 있는 URL이 표시됩니다.\n\n### 모니터링\n\nMCP 서버를 모니터링하려면 [Grafana](https://grafana.com/) 와 같은 호환되는 Prometheus 클라이언트를 사용할 수 있습니다. MCP 서버를 모니터링하는 방법은 [여기에서](./mcp-analytics/README.md) 확인하세요.","Korean","ko-KR",{"_29":62,"_33":66,"_38":67},{"_31":63,"_33":64,"_35":65},"MCP 服务器可从任何 MCP 客户端与 Tinybird Workspace 进行交互。","Tinybird MCP 服务器","# Tinybird MCP 服务器\n\n[![铁匠徽章](https://smithery.ai/badge/mcp-tinybird)](https://smithery.ai/server/@tinybirdco/mcp-tinybird)\n\nMCP 服务器可从任何 MCP 客户端与 Tinybird Workspace 进行交互。\n\n## 特征\n\n* 使用 Tinybird 查询 API 查询 Tinybird 数据源\n* 通过 HTTP 请求获取现有 Tinybird API 端点的结果\n* 推送数据文件\n\n它支持 SSE 和 STDIO 模式。\n\n## 使用示例\n\n* [Bluesky 指标](https://bsky.app/profile/alasdairb.com/post/3lbx2mq5urk22)（ [Claude 成绩单](https://www.tinybird.co/blog-posts/claude-analyze-bluesky-data-tinybird-mcp-server)）\n* [网络分析入门套件指标](https://github.com/tinybirdco/web-analytics-starter-kit)（[视频](https://x.com/alrocar/status/1861849648882688341)）\n\n## 设置\n\n### 安装\n\n#### 使用 MCP 包管理器\n\n**锻造工艺**\n\n要通过[Smithery](https://smithery.ai/protocol/mcp-tinybird)自动为 Claude Desktop 安装 Tinybird MCP：\n\n```bash\nnpx @smithery/cli install @tinybirdco/mcp-tinybird --client claude\n```\n\n**mcp-获取**\n\n您可以使用[mcp-get](https://github.com/michaellatman/mcp-get)安装 Tinybird MCP 服务器：\n\n```bash\nnpx @michaellatman/mcp-get@latest install mcp-tinybird\n```\n\n### 先决条件\n\nMCP 仍然非常新并且正在不断发展，我们建议遵循[MCP 文档](https://modelcontextprotocol.io/quickstart#prerequisites)来了解并运行 MCP 基础知识。\n\n你需要：\n\n* [Tinybird 帐户和工作区](https://www.tinybird.co/)\n* [克劳德桌面](https://claude.ai/)\n* [紫外线](https://docs.astral.sh/uv/getting-started/installation/)\n\n### 配置\n\n#### 1.配置Claude桌面\n\n根据您的操作系统创建以下文件：\n\n在 MacOS 上： `~/Library/Application Support/Claude/claude_desktop_config.json`\n\n在 Windows 上： `%APPDATA%/Claude/claude_desktop_config.json`\n\n将此模板粘贴到文件中，并将``和``替换为您的 Tinybird API URL 和管理令牌：\n\n```json\n{\n \"mcpServers\": {\n \"mcp-tinybird\": {\n \"command\": \"uvx\",\n \"args\": [\n \"mcp-tinybird\",\n \"stdio\"\n ],\n \"env\": {\n \"TB_API_URL\": \"\",\n \"TB_ADMIN_TOKEN\": \"\"\n }\n }\n }\n}\n```\n\n#### 2. 重启 Claude Desktop\n\n#### SSE 模式\n\n或者，您可以通过运行以下命令以 SSE 模式运行 MCP 服务器：\n\n```bash\nuvx mcp-tinybird sse\n```\n\n此模式对于与支持 SSE 的 MCP 客户端（如 Web 应用程序）集成很有用。\n\n## 提示\n\n服务器提供一个提示：\n\n* [tinybird-default](https://github.com/tinybirdco/mcp-tinybird/blob/93dd9e1d3c0e33f408fe88297151a44c1dfc049c/src/mcp-tinybird/server.py#L20) ：假设您已经在 Tinybird 中加载了一些数据并希望获得帮助来探索它。\n * 需要一个“主题”参数来定义您想要探索的数据的主题，例如“Bluesky 数据”或“零售销售”。\n\n您可以配置其他提示工作流程：\n\n* 使用此架构在您的工作区中创建一个提示数据源，并附加您的提示。MCP 会在初始化时加载`prompts` ，因此您可以根据需要进行配置：\n\n```bash\nSCHEMA >\n `name` String `json:$.name`,\n `description` String `json:$.description`,\n `timestamp` DateTime `json:$.timestamp`,\n `arguments` Array(String) `json:$.arguments[:]`,\n `prompt` String `json:$.prompt`\n```\n\n## 工具\n\n服务器实现了几个工具来与 Tinybird 工作区进行交互：\n\n* `list-data-sources` ：列出 Tinybird 工作区中的所有数据源\n* `list-pipes` ：列出 Tinybird 工作区中的所有管道端点\n* `get-data-source` ：根据名称获取数据源的信息，包括模式。\n* `get-pipe` ：根据名称获取管道端点的信息，包括其节点和 SQL 转换，以了解它提供的见解。\n* `request-pipe-data` ：通过 HTTP 请求从管道端点获取数据。管道端点可以包含参数来过滤分析数据。\n* `run-select-query` ：允许在数据源上运行选择查询以提取见解。\n* `append-insight` ：向备忘录资源添加新的业务洞察\n* `llms-tinybird-docs` ：包含整个 Tinybird 产品文档，因此您可以使用它来了解 Tinybird 是什么、它的作用、API 参考等。\n* `save-event` ：这允许向 Tinybird 数据源发送事件。使用它将用户生成的提示保存到提示数据源。MCP 服务器在初始化时从提示数据源获取数据，以便用户可以指示 LLM 遵循的工作流程。\n* `analyze-pipe` ：使用 Tinybird 分析 API 在 Pipe Endpoint 查询上运行 ClickHouse 解释，检查索引、排序键和分区键是否正在使用，并提出优化建议\n* `push-datafile` ：从本地数据文件在 Tinybird 工作区中创建远程数据源或管道。使用[文件系统 MCP](https://github.com/modelcontextprotocol/servers/tree/main/src/filesystem)保存此 MCP 服务器生成的文件。\n\n## 发展\n\n### 配置\n\n如果您在本地工作，请将两个环境变量添加到存储库根目录中的`.env`文件：\n\n```sh\nTB_API_URL=\nTB_ADMIN_TOKEN=\n```\n\n对于本地开发，请更新您的 Claude Desktop 配置：\n\n```json\n{\n \"mcpServers\": {\n \"mcp-tinybird_local\": {\n \"command\": \"uv\",\n \"args\": [\n \"--directory\",\n \"/path/to/your/mcp-tinybird\",\n \"run\",\n \"mcp-tinybird\",\n \"stdio\"\n ]\n }\n }\n}\n```\n\n```json\n\"mcpServers\": {\n \"mcp-tinybird\": {\n \"command\": \"uvx\",\n \"args\": [\n \"mcp-tinybird\"\n ]\n }\n}\n```\n\n### 构建和发布\n\n准备分发包：\n\n1. 同步依赖项并更新锁文件：\n\n```bash\nuv sync\n```\n\n2. 构建软件包分发版：\n\n```bash\nuv build\n```\n\n这将在`dist/`目录中创建源和轮子分布。\n\n3. 发布到 PyPI：\n\n```bash\nuv publish\n```\n\n注意：您需要通过环境变量或命令标志设置 PyPI 凭据：\n\n* 令牌： `--token`或`UV_PUBLISH_TOKEN`\n* 或用户名/密码： `--username` / `UV_PUBLISH_USERNAME`和`--password` / `UV_PUBLISH_PASSWORD`\n\n### 调试\n\n由于 MCP 服务器通过 stdio 运行，调试起来可能比较困难。为了获得最佳调试体验，我们强烈建议使用[MCP Inspector](https://github.com/modelcontextprotocol/inspector) 。\n\n您可以使用以下命令通过[`npm`](https://docs.npmjs.com/downloading-and-installing-node-js-and-npm)启动 MCP Inspector：\n\n```bash\nnpx @modelcontextprotocol/inspector uv --directory /Users/alrocar/gr/mcp-tinybird run mcp-tinybird\n```\n\n启动后，检查器将显示一个 URL，您可以在浏览器中访问该 URL 以开始调试。\n\n### 监控\n\n要监控 MCP 服务器，您可以使用任何兼容的 Prometheus 客户端，例如[Grafana](https://grafana.com/) 。点击[此处](./mcp-analytics/README.md)了解如何监控您的 MCP 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