[{"_1":2,"_916":-5,"_917":-5},"loaderData",{"_3":4,"_22":23,"_24":25,"_608":609},"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,"_81":-5,"_82":40,"_29":83,"_527":528,"_606":607},"availableLocales",[28,40,46,53,60,67,74],{"_29":30,"_33":37,"_38":39},"mcpServer",{"_31":32,"_33":34,"_35":36},"description","Eine Implementierung des Model Context Protocol (MCP)-Servers für SingleStore, die eine natürliche Sprachinteraktion mit SingleStore-Datenbanken über kompatible LLM-Clients wie Claude Desktop und Cursor ermöglicht.","name","SingleStore MCP Server","readme","# SingleStore MCP Server\n\n[![MIT-Lizenz](https://img.shields.io/badge/License-MIT-yellow.svg)](https://github.com/singlestore-labs/mcp-server-singlestore/blob/main/LICENSE) [![PyPI](https://img.shields.io/pypi/v/singlestore-mcp-server)](https://pypi.org/project/singlestore-mcp-server/) [![Downloads](https://static.pepy.tech/badge/singlestore-mcp-server)](https://pepy.tech/project/singlestore-mcp-server) [![Schmiedekunst](https://smithery.ai/badge/@singlestore-labs/mcp-server-singlestore)](https://smithery.ai/server/@singlestore-labs/mcp-server-singlestore)\n\n[Model Context Protocol]() (MCP) ist ein standardisiertes Protokoll zur Verwaltung des Kontexts zwischen großen Sprachmodellen (LLMs) und externen Systemen. Dieses Repository bietet ein Installationsprogramm und einen MCP-Server für Singlestore und ermöglicht so eine nahtlose Integration.\n\nMit MCP können Sie Claude Desktop, Cursor oder jeden kompatiblen MCP-Client verwenden, um mit SingleStore in natürlicher Sprache zu interagieren, was die mühelose Durchführung komplexer Vorgänge erleichtert.\n\n## Anforderungen\n\n* Python >= v3.11.0\n* [uvx](https://docs.astral.sh/uv/guides/tools/) in Ihrer Python-Umgebung installiert\n* Claude Desktop, Cursor oder ein anderer unterstützter LLM-Client\n\n## Client-Setup\n\n### 1. Init-Befehl\n\nDie einfachste Möglichkeit, den MCP-Server einzurichten, ist die Verwendung des Initialisierungsbefehls:\n\n```bash\nuvx singlestore-mcp-server init\n```\n\nDieser Befehl führt Folgendes aus:\n\n1. Authentifizieren des Benutzers\n2. Automatisches Suchen der Konfigurationsdatei für Ihre Plattform\n3. Erstellen oder aktualisieren Sie die Konfiguration, um den SingleStore MCP-Server einzuschließen\n4. Geben Sie Anweisungen zum Starten des Servers an\n\nSie können auch explizit einen `` übergeben:\n\n```bash\nuvx singlestore-mcp-server init \n```\n\nUm einen Client anzugeben (z. B. `claude` oder `cursor` ), verwenden Sie das Flag `--client` :\n\n```bash\nuvx singlestore-mcp-server init --client=\n```\n\n### 2. Installation über Smithery\n\nSo installieren Sie `mcp-server-singlestore` automatisch über [Smithery](https://smithery.ai/server/@singlestore-labs/mcp-server-singlestore) :\n\n```bash\nnpx -y @smithery/cli install @singlestore-labs/mcp-server-singlestore --client=\n```\n\nErsetzen Sie `` nach Bedarf durch `claude` oder `cursor` .\n\n### 3. Manuelle Konfiguration\n\n#### Claude Desktop und Cursor\n\n1. Fügen Sie Ihrer Client-Konfigurationsdatei die folgende Konfiguration hinzu:\n\n* [Claude Desktop](https://modelcontextprotocol.io/quickstart/user) :\n\n* [Cursor](https://docs.cursor.com/context/model-context-protocol#configuration-locations)\n\n ```json\n {\n \"mcpServers\": {\n \"singlestore-mcp-server\": {\n \"command\": \"uvx\",\n \"args\": [\n \"singlestore-mcp-server\",\n \"start\",\n \"\"\n ]\n }\n }\n }\n ```\n\n2. Starten Sie Ihren Client neu, nachdem Sie Änderungen an der Konfiguration vorgenommen haben.\n\n## Komponenten\n\n### Werkzeuge\n\nDer Server implementiert die folgenden Tools:\n\n* **workspace\\_groups\\_info** : Ruft Details zu den für den Benutzer zugänglichen Arbeitsbereichsgruppen ab\n * Keine Argumente erforderlich\n * Gibt Details der Arbeitsbereichsgruppen zurück\n* **workspaces\\_info** : Details zu den Arbeitsbereichen in einer bestimmten Arbeitsbereichsgruppe abrufen\n * Argumente: `workspaceGroupID` (Zeichenfolge)\n * Gibt Details zu den Arbeitsbereichen zurück\n* **organization\\_info** : Ruft Details zur aktuellen Organisation des Benutzers ab\n * Keine Argumente erforderlich\n * Gibt Details der Organisation zurück\n* **list\\_of\\_regions** : Ruft eine Liste aller Regionen ab, die Arbeitsbereiche für den Benutzer unterstützen\n * Keine Argumente erforderlich\n * Gibt eine Liste von Regionen zurück\n* **execute\\_sql** : Führen Sie SQL-Operationen in einem verbundenen Arbeitsbereich aus\n * Argumente: `workspace_group_identifier` , `workspace_identifier` , `username` , `password` , `database` , `sql_query`\n * Gibt die Ergebnisse der SQL-Abfrage in einem strukturierten Format zurück\n* **list\\_virtual\\_workspaces** : Listet alle für den Benutzer zugänglichen Starter-Arbeitsbereiche auf\n * Keine Argumente erforderlich\n * Gibt Details zu verfügbaren Starter-Arbeitsbereichen zurück\n* **create\\_virtual\\_workspace** : Erstellen Sie einen neuen Starter-Arbeitsbereich mit einem Benutzer\n * Argumente:\n * `name` : Name des Starter-Arbeitsbereichs\n * `database_name` : Name der zu erstellenden Datenbank\n * `username` : Benutzername für den Zugriff auf den Arbeitsbereich\n * `password` : Passwort für den Benutzer\n * `workspace_group` : Objekt mit `name` (optional) und `cellID` (obligatorisch)\n * Gibt Details zum erstellten Arbeitsbereich und Benutzer zurück\n* **execute\\_sql\\_on\\_virtual\\_workspace** : Führt SQL-Operationen auf einem virtuellen Arbeitsbereich aus\n * Argumente: `virtual_workspace_id` , `username` , `password` , `sql_query`\n * Gibt die Ergebnisse der SQL-Abfrage in einem strukturierten Format zurück, einschließlich Daten, Zeilenanzahl, Spalten und Status\n* **list\\_notebook\\_samples** : Listet alle in SingleStore Spaces verfügbaren Notebook-Beispiele auf\n * Keine Argumente erforderlich\n * Gibt Details zu verfügbaren Notebook-Beispielen zurück\n* **create\\_notebook** : Erstellt ein neues Notizbuch im persönlichen Bereich des Benutzers\n * Argumente: `notebook_name` , `content` (optional)\n * Gibt Details des erstellten Notebooks zurück\n* **list\\_personal\\_files** : Listet alle Dateien im persönlichen Bereich des Benutzers auf\n * Keine Argumente erforderlich\n * Gibt Details zu allen Dateien im persönlichen Bereich des Benutzers zurück\n* **create\\_scheduled\\_job** : Erstellen Sie einen neuen geplanten Job zum Ausführen eines Notebooks\n * Argumente:\n * `name` : Name für den Job\n * `notebook_path` : Pfad zum auszuführenden Notebook\n * `schedule_mode` : Einmalig oder Wiederkehrend\n * `execution_interval_minutes` : Minuten zwischen Ausführungen (optional)\n * `start_at` : Wann soll der Job gestartet werden (optional)\n * `description` : Beschreibung des Jobs (optional)\n * `create_snapshot` : Ob Notebook-Snapshots erstellt werden sollen (optional)\n * `runtime_name` : Name der Laufzeitumgebung\n * `parameters` : Parameter für den Job (optional)\n * `target_config` : Zielkonfiguration für den Job (optional)\n * Gibt Details zum erstellten Job zurück\n* **get\\_job\\_details** : Details zu einem bestimmten Job abrufen\n * Argumente: `job_id`\n * Gibt detaillierte Informationen zum angegebenen Job zurück\n* **list\\_job\\_executions** : Listet den Ausführungsverlauf für einen bestimmten Job auf\n * Argumente: `job_id` , `start` (optional), `end` (optional)\n * Gibt den Ausführungsverlauf für den angegebenen Job zurück\n\n## Dockerisierung\n\n### Erstellen des Docker-Images\n\nUm das Docker-Image für den MCP-Server zu erstellen, führen Sie den folgenden Befehl im Projektstammverzeichnis aus:\n\n```bash\ndocker build -t mcp-server-singlestore .\n```\n\n### Ausführen des Docker-Containers\n\nUm den Docker-Container auszuführen, verwenden Sie den folgenden Befehl:\n\n```bash\ndocker run -d \\\n -p 8080:8080 \\\n --name mcp-server \\\n mcp-server-singlestore\n```\n\n### Verwenden von Docker Secrets\n\nUm Geheimnisse sicher an den Container weiterzugeben, erstellen Sie ein Docker-Geheimnis und mounten Sie es:\n\n```bash\necho \"your-secret-value\" | docker secret create mcp_secret -\n```\n\nFühren Sie dann den Container mit dem Geheimnis aus:\n\n```bash\ndocker service create \\\n --name mcp-server \\\n --secret mcp_secret \\\n mcp-server-singlestore\n```","German","tag","de-DE",{"_29":41,"_33":44,"_38":45},{"_31":42,"_33":34,"_35":43},"An implementation of the Model Context Protocol (MCP) server for SingleStore that enables natural language interaction with SingleStore databases through compatible LLM clients like Claude Desktop and Cursor.","# SingleStore MCP Server\n\n[![MIT Licence](https://img.shields.io/badge/License-MIT-yellow.svg)](https://github.com/singlestore-labs/mcp-server-singlestore/blob/main/LICENSE) [![PyPI](https://img.shields.io/pypi/v/singlestore-mcp-server)](https://pypi.org/project/singlestore-mcp-server/) [![Downloads](https://static.pepy.tech/badge/singlestore-mcp-server)](https://pepy.tech/project/singlestore-mcp-server) [![Smithery](https://smithery.ai/badge/@singlestore-labs/mcp-server-singlestore)](https://smithery.ai/server/@singlestore-labs/mcp-server-singlestore)\n\n[Model Context Protocol]((https://modelcontextprotocol.io/introduction)) (MCP) is a standardized protocol designed to manage context between large language models (LLMs) and external systems. This repository provides an installer and an MCP Server for Singlestore, enabling seamless integration.\n\nWith MCP, you can use Claude Desktop, Cursor, or any compatible MCP client to interact with SingleStore using natural language, making it easier to perform complex operations effortlessly.\n\n## Requirements\n\n- Python >= v3.11.0\n- [uvx](https://docs.astral.sh/uv/guides/tools/) installed on your python environment\n- Claude Desktop, Cursor, or another supported LLM client\n\n\n## Client Setup\n\n### 1. Init Command\n\nThe simplest way to set up the MCP server is to use the initialization command:\n\n```bash\nuvx singlestore-mcp-server init\n```\n\nThis command will:\n\n1. Authenticate the user\n2. Automatically locate the configuration file for your platform\n3. Create or update the configuration to include the SingleStore MCP server\n4. Provide instructions for starting the server\n\nYou can also explicitly pass a ``:\n\n```bash\nuvx singlestore-mcp-server init \n```\n\nTo specify a client (e.g., `claude` or `cursor`), use the `--client` flag:\n\n```bash\nuvx singlestore-mcp-server init --client=\n```\n\n### 2. Installing via Smithery\n\nTo install `mcp-server-singlestore` automatically via [Smithery](https://smithery.ai/server/@singlestore-labs/mcp-server-singlestore):\n\n```bash\nnpx -y @smithery/cli install @singlestore-labs/mcp-server-singlestore --client=\n```\n\nReplace `` with `claude` or `cursor` as needed.\n\n### 3. Manual Configuration\n\n#### Claude Desktop and Cursor\n\n1. Add the following configuration to your client configuration file:\n\n- [Claude Desktop](https://modelcontextprotocol.io/quickstart/user):\n- [Cursor](https://docs.cursor.com/context/model-context-protocol#configuration-locations)\n\n ```json\n {\n \"mcpServers\": {\n \"singlestore-mcp-server\": {\n \"command\": \"uvx\",\n \"args\": [\n \"singlestore-mcp-server\",\n \"start\",\n \"\"\n ]\n }\n }\n }\n ```\n\n2. Restart your client after making changes to the configuration.\n\n## Components\n\n### Tools\n\nThe server implements the following tools:\n\n- **workspace_groups_info**: Retrieve details about the workspace groups accessible to the user\n - No arguments required\n - Returns details of the workspace groups\n- **workspaces_info**: Retrieve details about the workspaces in a specific workspace group\n - Arguments: `workspaceGroupID` (string)\n - Returns details of the workspaces\n- **organization_info**: Retrieve details about the user's current organization\n - No arguments required\n - Returns details of the organization\n- **list_of_regions**: Retrieve a list of all regions that support workspaces for the user\n - No arguments required\n - Returns a list of regions\n- **execute_sql**: Execute SQL operations on a connected workspace\n - Arguments: `workspace_group_identifier`, `workspace_identifier`, `username`, `password`, `database`, `sql_query`\n - Returns the results of the SQL query in a structured format\n- **list_virtual_workspaces**: List all starter workspaces accessible to the user\n - No arguments required\n - Returns details of available starter workspaces\n- **create_virtual_workspace**: Create a new starter workspace with a user\n - Arguments:\n - `name`: Name of the starter workspace\n - `database_name`: Name of the database to create\n - `username`: Username for accessing the workspace\n - `password`: Password for the user\n - `workspace_group`: Object containing `name` (optional) and `cellID` (mandatory)\n - Returns details of the created workspace and user\n- **execute_sql_on_virtual_workspace**: Execute SQL operations on a virtual workspace\n - Arguments: `virtual_workspace_id`, `username`, `password`, `sql_query`\n - Returns the results of the SQL query in a structured format including data, row count, columns, and status\n- **list_notebook_samples**: List all notebook samples available in SingleStore Spaces\n - No arguments required\n - Returns details of available notebook samples\n- **create_notebook**: Create a new notebook in the user's personal space\n - Arguments: `notebook_name`, `content` (optional)\n - Returns details of the created notebook\n- **list_personal_files**: List all files in the user's personal space\n - No arguments required\n - Returns details of all files in the user's personal space\n- **create_scheduled_job**: Create a new scheduled job to run a notebook\n - Arguments:\n - `name`: Name for the job\n - `notebook_path`: Path to the notebook to execute\n - `schedule_mode`: Once or Recurring\n - `execution_interval_minutes`: Minutes between executions (optional)\n - `start_at`: When to start the job (optional)\n - `description`: Description of the job (optional)\n - `create_snapshot`: Whether to create notebook snapshots (optional)\n - `runtime_name`: Name of the runtime environment\n - `parameters`: Parameters for the job (optional)\n - `target_config`: Target configuration for the job (optional)\n - Returns details of the created job\n- **get_job_details**: Get details about a specific job\n - Arguments: `job_id`\n - Returns detailed information about the specified job\n- **list_job_executions**: List execution history for a specific job\n - Arguments: `job_id`, `start` (optional), `end` (optional)\n - Returns execution history for the specified job\n\n## Dockerization\n\n### Building the Docker Image\n\nTo build the Docker image for the MCP server, run the following command in the project root:\n\n```bash\ndocker build -t mcp-server-singlestore .\n```\n\n### Running the Docker Container\n\nTo run the Docker container, use the following command:\n\n```bash\ndocker run -d \\\n -p 8080:8080 \\\n --name mcp-server \\\n mcp-server-singlestore\n```\n\n### Using Docker Secrets\n\nTo securely pass secrets to the container, create a Docker secret and mount it:\n\n```bash\necho \"your-secret-value\" | docker secret create mcp_secret -\n```\n\nThen, run the container with the secret:\n\n```bash\ndocker service create \\\n --name mcp-server \\\n --secret mcp_secret \\\n mcp-server-singlestore\n```\n","English","en-US",{"_29":47,"_33":51,"_38":52},{"_31":48,"_33":49,"_35":50},"Una implementación del servidor de Protocolo de contexto de modelo (MCP) para SingleStore que permite la interacción en lenguaje natural con las bases de datos de SingleStore a través de clientes LLM compatibles como Claude Desktop y Cursor.","Servidor MCP de SingleStore","# Servidor MCP de SingleStore\n\n[![Licencia MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://github.com/singlestore-labs/mcp-server-singlestore/blob/main/LICENSE) [![PyPI](https://img.shields.io/pypi/v/singlestore-mcp-server)](https://pypi.org/project/singlestore-mcp-server/) [![Descargas](https://static.pepy.tech/badge/singlestore-mcp-server)](https://pepy.tech/project/singlestore-mcp-server) [![Herrería](https://smithery.ai/badge/@singlestore-labs/mcp-server-singlestore)](https://smithery.ai/server/@singlestore-labs/mcp-server-singlestore)\n\n[El Protocolo de Contexto de Modelo]() (MCP) es un protocolo estandarizado diseñado para gestionar el contexto entre grandes modelos de lenguaje (LLM) y sistemas externos. Este repositorio proporciona un instalador y un servidor MCP para Singlestore, lo que permite una integración fluida.\n\nCon MCP, puedes usar Claude Desktop, Cursor o cualquier cliente MCP compatible para interactuar con SingleStore usando lenguaje natural, lo que facilita la realización de operaciones complejas sin esfuerzo.\n\n## Requisitos\n\n* Python >= v3.11.0\n* [uvx](https://docs.astral.sh/uv/guides/tools/) instalado en su entorno de Python\n* Claude Desktop, Cursor u otro cliente LLM compatible\n\n## Configuración del cliente\n\n### 1. Comando Init\n\nLa forma más sencilla de configurar el servidor MCP es utilizar el comando de inicialización:\n\n```bash\nuvx singlestore-mcp-server init\n```\n\nEste comando hará lo siguiente:\n\n1. Autenticar al usuario\n2. Localiza automáticamente el archivo de configuración para tu plataforma\n3. Cree o actualice la configuración para incluir el servidor SingleStore MCP\n4. Proporcionar instrucciones para iniciar el servidor\n\nTambién puedes pasar explícitamente una `` :\n\n```bash\nuvx singlestore-mcp-server init \n```\n\nPara especificar un cliente (por ejemplo, `claude` o `cursor` ), utilice el indicador `--client` :\n\n```bash\nuvx singlestore-mcp-server init --client=\n```\n\n### 2. Instalación mediante herrería\n\nPara instalar `mcp-server-singlestore` automáticamente a través de [Smithery](https://smithery.ai/server/@singlestore-labs/mcp-server-singlestore) :\n\n```bash\nnpx -y @smithery/cli install @singlestore-labs/mcp-server-singlestore --client=\n```\n\nReemplace `` con `claude` o `cursor` según sea necesario.\n\n### 3. Configuración manual\n\n#### Escritorio y cursor de Claude\n\n1. Agregue la siguiente configuración a su archivo de configuración de cliente:\n\n* [Escritorio de Claude](https://modelcontextprotocol.io/quickstart/user) :\n\n* [Cursor](https://docs.cursor.com/context/model-context-protocol#configuration-locations)\n\n ```json\n {\n \"mcpServers\": {\n \"singlestore-mcp-server\": {\n \"command\": \"uvx\",\n \"args\": [\n \"singlestore-mcp-server\",\n \"start\",\n \"\"\n ]\n }\n }\n }\n ```\n\n2. Reinicie su cliente después de realizar cambios en la configuración.\n\n## Componentes\n\n### Herramientas\n\nEl servidor implementa las siguientes herramientas:\n\n* **workspace\\_groups\\_info** : recupera detalles sobre los grupos de espacios de trabajo accesibles para el usuario\n * No se requieren argumentos\n * Devuelve detalles de los grupos de espacios de trabajo\n* **workspaces\\_info** : recupera detalles sobre los espacios de trabajo en un grupo de espacios de trabajo específico\n * Argumentos: `workspaceGroupID` (cadena)\n * Devuelve detalles de los espacios de trabajo.\n* **organization\\_info** : recupera detalles sobre la organización actual del usuario\n * No se requieren argumentos\n * Devuelve detalles de la organización.\n* **list\\_of\\_regions** : recupera una lista de todas las regiones que admiten espacios de trabajo para el usuario\n * No se requieren argumentos\n * Devuelve una lista de regiones\n* **execute\\_sql** : Ejecutar operaciones SQL en un espacio de trabajo conectado\n * Argumentos: `workspace_group_identifier` , `workspace_identifier` , `username` , `password` , `database` , `sql_query`\n * Devuelve los resultados de la consulta SQL en un formato estructurado\n* **list\\_virtual\\_workspaces** : enumera todos los espacios de trabajo de inicio accesibles para el usuario\n * No se requieren argumentos\n * Devuelve detalles de los espacios de trabajo de inicio disponibles\n* **create\\_virtual\\_workspace** : Crea un nuevo espacio de trabajo de inicio con un usuario\n * Argumentos:\n * `name` : Nombre del espacio de trabajo de inicio\n * `database_name` : Nombre de la base de datos a crear\n * `username` : Nombre de usuario para acceder al espacio de trabajo\n * `password` : Contraseña del usuario\n * `workspace_group` : Objeto que contiene `name` (opcional) y `cellID` (obligatorio)\n * Devuelve detalles del espacio de trabajo creado y del usuario.\n* **execute\\_sql\\_on\\_virtual\\_workspace** : Ejecutar operaciones SQL en un espacio de trabajo virtual\n * Argumentos: `virtual_workspace_id` , `username` , `password` , `sql_query`\n * Devuelve los resultados de la consulta SQL en un formato estructurado que incluye datos, recuento de filas, columnas y estado.\n* **list\\_notebook\\_samples** : Lista todos los ejemplos de cuadernos disponibles en SingleStore Spaces\n * No se requieren argumentos\n * Devuelve detalles de las muestras de cuadernos disponibles\n* **create\\_notebook** : Crea un nuevo cuaderno en el espacio personal del usuario\n * Argumentos: `notebook_name` , `content` (opcional)\n * Devuelve detalles del cuaderno creado\n* **list\\_personal\\_files** : enumera todos los archivos en el espacio personal del usuario\n * No se requieren argumentos\n * Devuelve detalles de todos los archivos en el espacio personal del usuario.\n* **create\\_scheduled\\_job** : crea un nuevo trabajo programado para ejecutar un cuaderno\n * Argumentos:\n * `name` : Nombre para el trabajo\n * `notebook_path` : Ruta al notebook a ejecutar\n * `schedule_mode` : Una vez o recurrente\n * `execution_interval_minutes` : Minutos entre ejecuciones (opcional)\n * `start_at` : Cuándo iniciar el trabajo (opcional)\n * `description` : Descripción del puesto de trabajo (opcional)\n * `create_snapshot` : Si se deben crear instantáneas del cuaderno (opcional)\n * `runtime_name` : Nombre del entorno de ejecución\n * `parameters` : Parámetros para el trabajo (opcional)\n * `target_config` : Configuración de destino para el trabajo (opcional)\n * Devuelve detalles del trabajo creado\n* **get\\_job\\_details** : Obtener detalles sobre un trabajo específico\n * Argumentos: `job_id`\n * Devuelve información detallada sobre el trabajo especificado\n* **list\\_job\\_executions** : enumera el historial de ejecución de un trabajo específico\n * Argumentos: `job_id` , `start` (opcional), `end` (opcional)\n * Devuelve el historial de ejecución del trabajo especificado\n\n## Dockerización\n\n### Construyendo la imagen de Docker\n\nPara crear la imagen de Docker para el servidor MCP, ejecute el siguiente comando en la raíz del proyecto:\n\n```bash\ndocker build -t mcp-server-singlestore .\n```\n\n### Ejecución del contenedor Docker\n\nPara ejecutar el contenedor Docker, utilice el siguiente comando:\n\n```bash\ndocker run -d \\\n -p 8080:8080 \\\n --name mcp-server \\\n mcp-server-singlestore\n```\n\n### Uso de Docker Secrets\n\nPara pasar secretos de forma segura al contenedor, cree un secreto de Docker y móntelo:\n\n```bash\necho \"your-secret-value\" | docker secret create mcp_secret -\n```\n\nLuego, ejecuta el contenedor con el secreto:\n\n```bash\ndocker service create \\\n --name mcp-server \\\n --secret mcp_secret \\\n mcp-server-singlestore\n```","Spanish","es-ES",{"_29":54,"_33":58,"_38":59},{"_31":55,"_33":56,"_35":57},"Claude Desktop や Cursor などの互換性のある LLM クライアントを通じて SingleStore データベースとの自然言語による対話を可能にする、SingleStore 用の Model Context Protocol (MCP) サーバーの実装。","シングルストア MCP サーバー","# シングルストア MCP サーバー\n\n[![MITライセンス](https://img.shields.io/badge/License-MIT-yellow.svg)](https://github.com/singlestore-labs/mcp-server-singlestore/blob/main/LICENSE) [![パイパイ](https://img.shields.io/pypi/v/singlestore-mcp-server)](https://pypi.org/project/singlestore-mcp-server/) [![ダウンロード](https://static.pepy.tech/badge/singlestore-mcp-server)](https://pepy.tech/project/singlestore-mcp-server) [![鍛冶屋](https://smithery.ai/badge/@singlestore-labs/mcp-server-singlestore)](https://smithery.ai/server/@singlestore-labs/mcp-server-singlestore)\n\n[モデルコンテキストプロトコル]()（MCP）は、大規模言語モデル（LLM）と外部システム間のコンテキストを管理するために設計された標準化されたプロトコルです。このリポジトリは、Singlestore用のインストーラーとMCPサーバーを提供し、シームレスな統合を実現します。\n\nMCP を使用すると、Claude Desktop、Cursor、または互換性のある MCP クライアントを使用して自然言語で SingleStore と対話できるため、複雑な操作を簡単に実行できます。\n\n## 要件\n\n* Python >= v3.11.0\n* Python環境に[uvx](https://docs.astral.sh/uv/guides/tools/)がインストールされている\n* Claude Desktop、Cursor、またはサポートされている他のLLMクライアント\n\n## クライアントのセットアップ\n\n### 1. 初期化コマンド\n\nMCP サーバーをセットアップする最も簡単な方法は、初期化コマンドを使用することです。\n\n```bash\nuvx singlestore-mcp-server init\n```\n\nこのコマンドは次のことを行います。\n\n1. ユーザーを認証する\n2. プラットフォームの設定ファイルを自動的に見つける\n3. SingleStore MCP サーバーを含むように構成を作成または更新します\n4. サーバーの起動手順を説明します\n\n``を明示的に渡すこともできます。\n\n```bash\nuvx singlestore-mcp-server init \n```\n\nクライアント (例: `claude`または`cursor` ) を指定するには、 `--client`フラグを使用します。\n\n```bash\nuvx singlestore-mcp-server init --client=\n```\n\n### 2. Smithery経由でインストールする\n\n[Smithery](https://smithery.ai/server/@singlestore-labs/mcp-server-singlestore)経由で`mcp-server-singlestore`自動的にインストールするには:\n\n```bash\nnpx -y @smithery/cli install @singlestore-labs/mcp-server-singlestore --client=\n```\n\n必要に応じて、 ``を`claude`または`cursor`に置き換えます。\n\n### 3. 手動設定\n\n#### クロード・デスクトップとカーソル\n\n1. クライアント構成ファイルに次の構成を追加します。\n\n* [クロードデスクトップ](https://modelcontextprotocol.io/quickstart/user):\n\n* [カーソル](https://docs.cursor.com/context/model-context-protocol#configuration-locations)\n\n ```json\n {\n \"mcpServers\": {\n \"singlestore-mcp-server\": {\n \"command\": \"uvx\",\n \"args\": [\n \"singlestore-mcp-server\",\n \"start\",\n \"\"\n ]\n }\n }\n }\n ```\n\n2. 設定を変更した後は、クライアントを再起動してください。\n\n## コンポーネント\n\n### ツール\n\nサーバーは次のツールを実装します。\n\n* **workspace\\_groups\\_info** : ユーザーがアクセスできるワークスペースグループの詳細を取得します。\n * 引数は必要ありません\n * ワークスペースグループの詳細を返します\n* **workspaces\\_info** : 特定のワークスペースグループ内のワークスペースの詳細を取得します。\n * 引数: `workspaceGroupID` (文字列)\n * ワークスペースの詳細を返します\n* **organization\\_info** : ユーザーの現在の組織に関する詳細を取得します\n * 引数は必要ありません\n * 組織の詳細を返します\n* **list\\_of\\_regions** : ユーザーのワークスペースをサポートするすべてのリージョンのリストを取得します。\n * 引数は必要ありません\n * 地域のリストを返します\n* **execute\\_sql** : 接続されたワークスペースでSQL操作を実行する\n * 引数: `workspace_group_identifier` 、 `workspace_identifier` 、 `username` 、 `password` 、 `database` 、 `sql_query`\n * SQLクエリの結果を構造化された形式で返します\n* **list\\_virtual\\_workspaces** : ユーザーがアクセスできるすべてのスターターワークスペースを一覧表示します\n * 引数は必要ありません\n * 利用可能なスターターワークスペースの詳細を返します\n* **create\\_virtual\\_workspace** : ユーザーで新しいスターターワークスペースを作成する\n * 引数:\n * `name` : スターターワークスペースの名前\n * `database_name` : 作成するデータベースの名前\n * `username` : ワークスペースにアクセスするためのユーザー名\n * `password` : ユーザーのパスワード\n * `workspace_group` : `name` （オプション）と`cellID` （必須）を含むオブジェクト\n * 作成されたワークスペースとユーザーの詳細を返します\n* **execute\\_sql\\_on\\_virtual\\_workspace** : 仮想ワークスペースでSQL操作を実行する\n * 引数: `virtual_workspace_id` 、 `username` 、 `password` 、 `sql_query`\n * データ、行数、列、ステータスを含む構造化された形式でSQLクエリの結果を返します。\n* **list\\_notebook\\_samples** : SingleStore Spaces で利用可能なすべてのノートブックのサンプルを一覧表示します\n * 引数は必要ありません\n * 利用可能なノートブックのサンプルの詳細を返します\n* **create\\_notebook** : ユーザーの個人スペースに新しいノートブックを作成する\n * 引数: `notebook_name` 、 `content` （オプション）\n * 作成されたノートブックの詳細を返します\n* **list\\_personal\\_files** : ユーザーの個人スペース内のすべてのファイルを一覧表示する\n * 引数は必要ありません\n * ユーザーの個人スペースにあるすべてのファイルの詳細を返します\n* **create\\_scheduled\\_job** : ノートブックを実行するための新しいスケジュールされたジョブを作成する\n * 引数:\n * `name` : ジョブの名前\n * `notebook_path` : 実行するノートブックへのパス\n * `schedule_mode` : 1回または定期\n * `execution_interval_minutes` : 実行間隔（分）（オプション）\n * `start_at` : ジョブを開始するタイミング（オプション）\n * `description` : ジョブの説明（オプション）\n * `create_snapshot` : ノートブックのスナップショットを作成するかどうか（オプション）\n * `runtime_name`環境の名前\n * `parameters` : ジョブのパラメータ（オプション）\n * `target_config` : ジョブのターゲット構成（オプション）\n * 作成されたジョブの詳細を返します\n* **get\\_job\\_details** : 特定のジョブの詳細を取得する\n * 引数: `job_id`\n * 指定されたジョブの詳細情報を返します\n* **list\\_job\\_executions** : 特定のジョブの実行履歴を一覧表示する\n * 引数: `job_id` 、 `start` （オプション）、 `end` （オプション）\n * 指定されたジョブの実行履歴を返します\n\n## ドッカー化\n\n### Dockerイメージの構築\n\nMCP サーバーの Docker イメージをビルドするには、プロジェクトルートで次のコマンドを実行します。\n\n```bash\ndocker build -t mcp-server-singlestore .\n```\n\n### Dockerコンテナの実行\n\nDocker コンテナを実行するには、次のコマンドを使用します。\n\n```bash\ndocker run -d \\\n -p 8080:8080 \\\n --name mcp-server \\\n mcp-server-singlestore\n```\n\n### Docker Secretsの使用\n\nシークレットをコンテナに安全に渡すには、Docker シークレットを作成してマウントします。\n\n```bash\necho \"your-secret-value\" | docker secret create mcp_secret -\n```\n\n次に、シークレットを使用してコンテナを実行します。\n\n```bash\ndocker service create \\\n --name mcp-server \\\n --secret mcp_secret \\\n mcp-server-singlestore\n```","Japanese","ja-JP",{"_29":61,"_33":65,"_38":66},{"_31":62,"_33":63,"_35":64},"Claude Desktop 및 Cursor와 같은 호환 가능한 LLM 클라이언트를 통해 SingleStore 데이터베이스와 자연어 상호 작용을 가능하게 하는 SingleStore용 MCP(Model Context Protocol) 서버 구현입니다.","SingleStore MCP 서버","# SingleStore MCP 서버\n\n[![MIT 라이센스](https://img.shields.io/badge/License-MIT-yellow.svg)](https://github.com/singlestore-labs/mcp-server-singlestore/blob/main/LICENSE) [![파이파이](https://img.shields.io/pypi/v/singlestore-mcp-server)](https://pypi.org/project/singlestore-mcp-server/) [![다운로드](https://static.pepy.tech/badge/singlestore-mcp-server)](https://pepy.tech/project/singlestore-mcp-server) [![대장간](https://smithery.ai/badge/@singlestore-labs/mcp-server-singlestore)](https://smithery.ai/server/@singlestore-labs/mcp-server-singlestore)\n\n[모델 컨텍스트 프로토콜]() (MCP)은 대규모 언어 모델(LLM)과 외부 시스템 간의 컨텍스트를 관리하도록 설계된 표준화된 프로토콜입니다. 이 저장소는 Singlestore용 설치 프로그램과 MCP 서버를 제공하여 원활한 통합을 지원합니다.\n\nMCP를 사용하면 Claude Desktop, Cursor 또는 호환되는 모든 MCP 클라이언트를 사용하여 자연어로 SingleStore와 상호 작용할 수 있으므로 복잡한 작업을 손쉽게 수행할 수 있습니다.\n\n## 요구 사항\n\n* 파이썬 >= v3.11.0\n* 파이썬 환경에 [uvx가](https://docs.astral.sh/uv/guides/tools/) 설치되어 있습니다\n* Claude Desktop, Cursor 또는 다른 지원되는 LLM 클라이언트\n\n## 클라이언트 설정\n\n### 1. Init 명령\n\nMCP 서버를 설정하는 가장 간단한 방법은 초기화 명령을 사용하는 것입니다.\n\n지엑스피1\n\n이 명령은 다음을 수행합니다.\n\n1. 사용자 인증\n2. 플랫폼에 맞는 구성 파일을 자동으로 찾습니다.\n3. SingleStore MCP 서버를 포함하도록 구성을 생성하거나 업데이트합니다.\n4. 서버 시작에 대한 지침을 제공합니다\n\n`` 명시적으로 전달할 수도 있습니다.\n\n```bash\nuvx singlestore-mcp-server init \n```\n\n클라이언트(예: `claude` 또는 `cursor` )를 지정하려면 `--client` 플래그를 사용합니다.\n\n```bash\nuvx singlestore-mcp-server init --client=\n```\n\n### 2. Smithery를 통한 설치\n\n[Smithery](https://smithery.ai/server/@singlestore-labs/mcp-server-singlestore) 를 통해 `mcp-server-singlestore` 자동으로 설치하려면:\n\n```bash\nnpx -y @smithery/cli install @singlestore-labs/mcp-server-singlestore --client=\n```\n\n필요에 따라 `` `claude` 나 `cursor` 로 바꾸세요.\n\n### 3. 수동 구성\n\n#### 클로드 데스크탑과 커서\n\n1. 클라이언트 구성 파일에 다음 구성을 추가합니다.\n\n* [클로드 데스크탑](https://modelcontextprotocol.io/quickstart/user) :\n\n* [커서](https://docs.cursor.com/context/model-context-protocol#configuration-locations)\n\n ```json\n {\n \"mcpServers\": {\n \"singlestore-mcp-server\": {\n \"command\": \"uvx\",\n \"args\": [\n \"singlestore-mcp-server\",\n \"start\",\n \"\"\n ]\n }\n }\n }\n ```\n\n2. 구성을 변경한 후 클라이언트를 다시 시작합니다.\n\n## 구성 요소\n\n### 도구\n\n서버는 다음 도구를 구현합니다.\n\n* **workspace\\_groups\\_info** : 사용자가 액세스할 수 있는 작업 공간 그룹에 대한 세부 정보를 검색합니다.\n * 인수가 필요하지 않습니다\n * 작업 공간 그룹의 세부 정보를 반환합니다.\n* **workspaces\\_info** : 특정 작업 공간 그룹의 작업 공간에 대한 세부 정보를 검색합니다.\n * 인수: `workspaceGroupID` (문자열)\n * 작업 공간의 세부 정보를 반환합니다.\n* **organization\\_info** : 사용자의 현재 조직에 대한 세부 정보를 검색합니다.\n * 인수가 필요하지 않습니다\n * 조직의 세부 정보를 반환합니다.\n* **list\\_of\\_regions** : 사용자의 작업 공간을 지원하는 모든 지역 목록을 검색합니다.\n * 인수가 필요하지 않습니다\n * 지역 목록을 반환합니다.\n* **execute\\_sql** : 연결된 작업 공간에서 SQL 작업 실행\n * 인수: `workspace_group_identifier` , `workspace_identifier` 식별자, `username` , `password` , `database` , `sql_query`\n * 구조화된 형식으로 SQL 쿼리 결과를 반환합니다.\n* **list\\_virtual\\_workspaces** : 사용자가 액세스할 수 있는 모든 시작 작업 공간을 나열합니다.\n * 인수가 필요하지 않습니다\n * 사용 가능한 시작 작업 공간의 세부 정보를 반환합니다.\n* **create\\_virtual\\_workspace** : 사용자로 새로운 시작 작업 공간을 만듭니다.\n * 인수:\n * `name` : 스타터 작업 공간의 이름\n * `database_name` : 생성할 데이터베이스의 이름\n * `username` : 작업 공간에 액세스하기 위한 사용자 이름\n * `password` : 사용자의 비밀번호\n * `workspace_group` : `name` (선택 사항)과 `cellID` (필수)를 포함하는 객체\n * 생성된 작업 공간 및 사용자의 세부 정보를 반환합니다.\n* **execute\\_sql\\_on\\_virtual\\_workspace** : 가상 작업 공간에서 SQL 작업 실행\n * 인수: `virtual_workspace_id` , `username` , `password` , `sql_query`\n * 데이터, 행 수, 열 및 상태를 포함하는 구조화된 형식으로 SQL 쿼리 결과를 반환합니다.\n* **list\\_notebook\\_samples** : SingleStore Spaces에서 사용 가능한 모든 노트북 샘플을 나열합니다.\n * 인수가 필요하지 않습니다\n * 사용 가능한 노트북 샘플의 세부 정보를 반환합니다.\n* **create\\_notebook** : 사용자의 개인 공간에 새로운 노트북을 생성합니다.\n * 인수: `notebook_name` , `content` (선택 사항)\n * 생성된 노트북의 세부 정보를 반환합니다.\n* **list\\_personal\\_files** : 사용자 개인 공간에 있는 모든 파일을 나열합니다.\n * 인수가 필요하지 않습니다\n * 사용자의 개인 공간에 있는 모든 파일의 세부 정보를 반환합니다.\n* **create\\_scheduled\\_job** : 노트북을 실행하기 위한 새로운 예약된 작업을 생성합니다.\n * 인수:\n * `name` : 직업 이름\n * `notebook_path` : 실행할 notebook의 경로\n * `schedule_mode` : 한 번 또는 반복\n * `execution_interval_minutes` : 실행 간 간격(분) (선택 사항)\n * `start_at` : 작업을 시작할 시점(선택 사항)\n * `description` : 직무 설명 (선택 사항)\n * `create_snapshot` : 노트북 스냅샷을 생성할지 여부(선택 사항)\n * `runtime_name` : 런타임 환경의 이름\n * `parameters` : 작업에 대한 매개변수(선택 사항)\n * `target_config` : 작업에 대한 대상 구성(선택 사항)\n * 생성된 작업의 세부 정보를 반환합니다.\n* **get\\_job\\_details** : 특정 직업에 대한 세부 정보를 가져옵니다.\n * 인수: `job_id`\n * 지정된 작업에 대한 자세한 정보를 반환합니다.\n* **list\\_job\\_executions** : 특정 작업에 대한 실행 기록을 나열합니다.\n * 인수: `job_id` , `start` (선택 사항), `end` (선택 사항)\n * 지정된 작업에 대한 실행 기록을 반환합니다.\n\n## 도커화\n\n### Docker 이미지 빌드\n\nMCP 서버용 Docker 이미지를 빌드하려면 프로젝트 루트에서 다음 명령을 실행하세요.\n\n```bash\ndocker build -t mcp-server-singlestore .\n```\n\n### Docker 컨테이너 실행\n\nDocker 컨테이너를 실행하려면 다음 명령을 사용하세요.\n\n```bash\ndocker run -d \\\n -p 8080:8080 \\\n --name mcp-server \\\n mcp-server-singlestore\n```\n\n### Docker Secrets 사용\n\n컨테이너에 비밀을 안전하게 전달하려면 Docker 비밀을 생성하고 마운트하세요.\n\n```bash\necho \"your-secret-value\" | docker secret create mcp_secret -\n```\n\n그런 다음 비밀을 사용하여 컨테이너를 실행합니다.\n\n```bash\ndocker service create \\\n --name mcp-server \\\n --secret mcp_secret \\\n mcp-server-singlestore\n```","Korean","ko-KR",{"_29":68,"_33":72,"_38":73},{"_31":69,"_33":70,"_35":71},"Реализация сервера Model Context Protocol (MCP) для SingleStore, обеспечивающая взаимодействие на естественном языке с базами данных SingleStore через совместимые клиенты LLM, такие как Claude Desktop и Cursor.","Сервер SingleStore MCP","# Сервер SingleStore MCP\n\n[![Лицензия Массачусетского технологического института](https://img.shields.io/badge/License-MIT-yellow.svg)](https://github.com/singlestore-labs/mcp-server-singlestore/blob/main/LICENSE) [![PyPI](https://img.shields.io/pypi/v/singlestore-mcp-server)](https://pypi.org/project/singlestore-mcp-server/) [![Загрузки](https://static.pepy.tech/badge/singlestore-mcp-server)](https://pepy.tech/project/singlestore-mcp-server) [![Кузнечное дело](https://smithery.ai/badge/@singlestore-labs/mcp-server-singlestore)](https://smithery.ai/server/@singlestore-labs/mcp-server-singlestore)\n\n[Model Context Protocol]() (MCP) — это стандартизированный протокол, предназначенный для управления контекстом между большими языковыми моделями (LLM) и внешними системами. Этот репозиторий предоставляет установщик и сервер MCP для Singlestore, обеспечивая бесшовную интеграцию.\n\nС помощью MCP вы можете использовать Claude Desktop, Cursor или любой совместимый клиент MCP для взаимодействия с SingleStore с помощью естественного языка, что упрощает выполнение сложных операций.\n\n## Требования\n\n* Питон >= v3.11.0\n* [uvx](https://docs.astral.sh/uv/guides/tools/) установлен в вашей среде Python\n* Claude Desktop, Cursor или другой поддерживаемый клиент LLM\n\n## Настройка клиента\n\n### 1. Команда инициализации\n\nСамый простой способ настройки сервера MCP — использовать команду инициализации:\n\n```bash\nuvx singlestore-mcp-server init\n```\n\nЭта команда выполнит:\n\n1. Аутентификация пользователя\n2. Автоматически находит файл конфигурации для вашей платформы\n3. Создайте или обновите конфигурацию, включив в нее сервер SingleStore MCP.\n4. Предоставьте инструкции по запуску сервера\n\nВы также можете явно передать `` :\n\n```bash\nuvx singlestore-mcp-server init \n```\n\nЧтобы указать клиента (например, `claude` или `cursor` ), используйте флаг `--client` :\n\n```bash\nuvx singlestore-mcp-server init --client=\n```\n\n### 2. Установка через Smithery\n\nДля автоматической установки `mcp-server-singlestore` через [Smithery](https://smithery.ai/server/@singlestore-labs/mcp-server-singlestore) :\n\n```bash\nnpx -y @smithery/cli install @singlestore-labs/mcp-server-singlestore --client=\n```\n\nПри необходимости замените `` на `claude` или `cursor` .\n\n### 3. Ручная настройка\n\n#### Рабочий стол Клода и курсор\n\n1. Добавьте следующую конфигурацию в файл конфигурации клиента:\n\n* [Клод Рабочий стол](https://modelcontextprotocol.io/quickstart/user) :\n\n* [Курсор](https://docs.cursor.com/context/model-context-protocol#configuration-locations)\n\n ```json\n {\n \"mcpServers\": {\n \"singlestore-mcp-server\": {\n \"command\": \"uvx\",\n \"args\": [\n \"singlestore-mcp-server\",\n \"start\",\n \"\"\n ]\n }\n }\n }\n ```\n\n2. Перезапустите клиент после внесения изменений в конфигурацию.\n\n## Компоненты\n\n### Инструменты\n\nНа сервере реализованы следующие инструменты:\n\n* **workspace\\_groups\\_info** : получение сведений о группах рабочего пространства, доступных пользователю\n * Аргументы не требуются\n * Возвращает сведения о группах рабочего пространства\n* **workspaces\\_info** : получение сведений о рабочих пространствах в определенной группе рабочих пространств\n * Аргументы: `workspaceGroupID` (строка)\n * Возвращает сведения о рабочих пространствах\n* **organization\\_info** : Получить сведения о текущей организации пользователя\n * Аргументы не требуются\n * Возвращает данные организации\n* **list\\_of\\_regions** : Получить список всех регионов, которые поддерживают рабочие пространства для пользователя.\n * Аргументы не требуются\n * Возвращает список регионов\n* **execute\\_sql** : выполнение операций SQL в подключенной рабочей области\n * Аргументы: `workspace_group_identifier` , `workspace_identifier` , `username` , `password` , `database` , `sql_query`\n * Возвращает результаты SQL-запроса в структурированном формате.\n* **list\\_virtual\\_workspaces** : список всех начальных рабочих пространств, доступных пользователю.\n * Аргументы не требуются\n * Возвращает сведения о доступных начальных рабочих пространствах\n* **create\\_virtual\\_workspace** : создать новое начальное рабочее пространство с пользователем\n * Аргументы:\n * `name` : Имя стартовой рабочей области\n * `database_name` : Имя создаваемой базы данных\n * `username` : Имя пользователя для доступа к рабочему пространству\n * `password` : Пароль для пользователя\n * `workspace_group` : объект, содержащий `name` (необязательно) и `cellID` (обязательно)\n * Возвращает сведения о созданном рабочем пространстве и пользователе.\n* **execute\\_sql\\_on\\_virtual\\_workspace** : выполнение операций SQL в виртуальном рабочем пространстве\n * Аргументы: `virtual_workspace_id` , `username` , `password` , `sql_query`\n * Возвращает результаты SQL-запроса в структурированном формате, включая данные, количество строк, столбцы и статус.\n* **list\\_notebook\\_samples** : список всех образцов блокнотов, доступных в SingleStore Spaces\n * Аргументы не требуются\n * Возвращает сведения о доступных образцах блокнотов\n* **create\\_notebook** : Создать новый блокнот в личном пространстве пользователя.\n * Аргументы: `notebook_name` , `content` (необязательно)\n * Возвращает сведения о созданном блокноте.\n* **list\\_personal\\_files** : Список всех файлов в личном пространстве пользователя.\n * Аргументы не требуются\n * Возвращает сведения обо всех файлах в личном пространстве пользователя.\n* **create\\_scheduled\\_job** : Создать новое запланированное задание для запуска блокнота\n * Аргументы:\n * `name` : Имя для работы\n * `notebook_path` : Путь к блокноту для выполнения\n * `schedule_mode` : однократно или повторяющееся\n * `execution_interval_minutes` : Минуты между выполнениями (необязательно)\n * `start_at` : Когда начинать работу (необязательно)\n * `description` : Описание работы (необязательно)\n * `create_snapshot` : создавать ли снимки блокнота (необязательно)\n * `runtime_name` : Имя среды выполнения\n * `parameters` : Параметры задания (необязательно)\n * `target_config` : Целевая конфигурация для задания (необязательно)\n * Возвращает сведения о созданной работе\n* **get\\_job\\_details** : Получить сведения о конкретной работе\n * Аргументы: `job_id`\n * Возвращает подробную информацию об указанной работе\n* **list\\_job\\_executions** : Список истории выполнения для определенного задания\n * Аргументы: `job_id` , `start` (необязательно), `end` (необязательно)\n * Возвращает историю выполнения указанного задания.\n\n## Докеризация\n\n### Создание образа Docker\n\nЧтобы создать образ Docker для сервера MCP, выполните следующую команду в корне проекта:\n\n```bash\ndocker build -t mcp-server-singlestore .\n```\n\n### Запуск Docker-контейнера\n\nДля запуска контейнера Docker используйте следующую команду:\n\n```bash\ndocker run -d \\\n -p 8080:8080 \\\n --name mcp-server \\\n mcp-server-singlestore\n```\n\n### Использование Docker-секретов\n\nЧтобы безопасно передать секреты в контейнер, создайте секрет Docker и смонтируйте его:\n\n```bash\necho \"your-secret-value\" | docker secret create mcp_secret -\n```\n\nЗатем запустите контейнер с секретом:\n\n```bash\ndocker service create \\\n --name mcp-server \\\n --secret mcp_secret \\\n mcp-server-singlestore\n```","Russian","ru-RU",{"_29":75,"_33":79,"_38":80},{"_31":76,"_33":77,"_35":78},"SingleStore 的模型上下文协议 (MCP) 服务器的实现，可通过兼容的 LLM 客户端（如 Claude Desktop 和 Cursor）实现与 SingleStore 数据库的自然语言交互。","单店 MCP 服务器","# 单店 MCP 服务器\n\n[![MIT许可证](https://img.shields.io/badge/License-MIT-yellow.svg)](https://github.com/singlestore-labs/mcp-server-singlestore/blob/main/LICENSE) [![PyPI](https://img.shields.io/pypi/v/singlestore-mcp-server)](https://pypi.org/project/singlestore-mcp-server/) [![下载](https://static.pepy.tech/badge/singlestore-mcp-server)](https://pepy.tech/project/singlestore-mcp-server) [![锻造工艺](https://smithery.ai/badge/@singlestore-labs/mcp-server-singlestore)](https://smithery.ai/server/@singlestore-labs/mcp-server-singlestore)\n\n[模型上下文协议]()(MCP) 是一种标准化协议，旨在管理大型语言模型 (LLM) 与外部系统之间的上下文。此存储库为 Singlestore 提供了安装程序和 MCP 服务器，可实现无缝集成。\n\n通过 MCP，您可以使用 Claude Desktop、Cursor 或任何兼容的 MCP 客户端通过自然语言与 SingleStore 进行交互，从而更轻松地执行复杂的操作。\n\n## 要求\n\n* Python >= v3.11.0\n* [uvx](https://docs.astral.sh/uv/guides/tools/)安装在你的 Python 环境中\n* Claude Desktop、Cursor 或其他受支持的 LLM 客户端\n\n## 客户端设置\n\n### 1. Init 命令\n\n设置 MCP 服务器最简单的方法是使用初始化命令：\n\n```bash\nuvx singlestore-mcp-server init\n```\n\n此命令将：\n\n1. 验证用户身份\n2. 自动定位适合您平台的配置文件\n3. 创建或更新配置以包含 SingleStore MCP 服务器\n4. 提供启动服务器的说明\n\n您还可以明确传递`` ：\n\n```bash\nuvx singlestore-mcp-server init \n```\n\n要指定客户端（例如， `claude`或`cursor` ），请使用`--client`标志：\n\n```bash\nuvx singlestore-mcp-server init --client=\n```\n\n### 2.通过 Smithery 安装\n\n要通过[Smithery](https://smithery.ai/server/@singlestore-labs/mcp-server-singlestore)自动安装`mcp-server-singlestore` ：\n\n```bash\nnpx -y @smithery/cli install @singlestore-labs/mcp-server-singlestore --client=\n```\n\n根据需要将``替换为`claude`或`cursor` 。\n\n### 3.手动配置\n\n#### Claude 桌面和光标\n\n1. 将以下配置添加到您的客户端配置文件中：\n\n* [克劳德桌面](https://modelcontextprotocol.io/quickstart/user)：\n\n* [光标](https://docs.cursor.com/context/model-context-protocol#configuration-locations)\n\n ```json\n {\n \"mcpServers\": {\n \"singlestore-mcp-server\": {\n \"command\": \"uvx\",\n \"args\": [\n \"singlestore-mcp-server\",\n \"start\",\n \"\"\n ]\n }\n }\n }\n ```\n\n2. 更改配置后重新启动客户端。\n\n## 成分\n\n### 工具\n\n该服务器实现了以下工具：\n\n* **workspace\\_groups\\_info** ：检索有关用户可访问的工作区组的详细信息\n * 无需任何参数\n * 返回工作区组的详细信息\n* **jobs\\_info** ：检索有关特定工作区组中的工作区的详细信息\n * 参数： `workspaceGroupID` （字符串）\n * 返回工作区的详细信息\n* **organization\\_info** ：检索有关用户当前组织的详细信息\n * 无需任何参数\n * 返回组织的详细信息\n* **list\\_of\\_regions** ：检索支持用户工作区的所有区域的列表\n * 无需任何参数\n * 返回区域列表\n* **执行**SQL 操作：在连接的工作区上执行 SQL 操作\n * 参数： `workspace_group_identifier` 、 `workspace_identifier` 、 `username` 、 `password` 、 `database` 、 `sql_query`\n * 以结构化格式返回 SQL 查询的结果\n* **list\\_virtual\\_workspaces** ：列出用户可访问的所有启动工作区\n * 无需任何参数\n * 返回可用启动工作区的详细信息\n* **create\\_virtual\\_workspace** ：为用户创建一个新的启动工作区\n * 参数：\n * `name` ：启动工作区的名称\n * `database_name` ：要创建的数据库的名称\n * `username` ：访问工作区的用户名\n * `password` ：用户密码\n * `workspace_group` ：包含`name` （可选）和`cellID` （强制）的对象\n * 返回已创建的工作区和用户的详细信息\n* **execute\\_sql\\_on\\_virtual\\_workspace** ：在虚拟工作区上执行 SQL 操作\n * 参数： `virtual_workspace_id` 、 `username` 、 `password` 、 `sql_query`\n * 以结构化格式返回 SQL 查询的结果，包括数据、行数、列和状态\n* **list\\_notebook\\_samples** ：列出 SingleStore Spaces 中可用的所有笔记本示例\n * 无需任何参数\n * 返回可用笔记本样本的详细信息\n* **create\\_notebook** ：在用户个人空间创建一个新的笔记本\n * 参数： `notebook_name` 、 `content` （可选）\n * 返回已创建笔记本的详细信息\n* **list\\_personal\\_files** ：列出用户个人空间中的所有文件\n * 无需任何参数\n * 返回用户个人空间中所有文件的详细信息\n* **create\\_scheduled\\_job** ：创建一个新的计划作业来运行笔记本\n * 参数：\n * `name` ：工作名称\n * `notebook_path` ：要执行的笔记本的路径\n * `schedule_mode` ：一次或重复\n * `execution_interval_minutes` ：执行间隔分钟数（可选）\n * `start_at` ：何时开始工作（可选）\n * `description` ：工作描述（可选）\n * `create_snapshot` ：是否创建笔记本快照（可选）\n * `runtime_name` ：运行时环境的名称\n * `parameters` ：作业的参数（可选）\n * `target_config` ：作业的目标配置（可选）\n * 返回已创建作业的详细信息\n* **get\\_job\\_details** ：获取特定工作的详细信息\n * 参数： `job_id`\n * 返回指定作业的详细信息\n* **list\\_job\\_executions** ：列出特定作业的执行历史记录\n * 参数： `job_id` 、 `start` （可选）、 `end` （可选）\n * 返回指定作业的执行历史记录\n\n## Docker化\n\n### 构建 Docker 镜像\n\n要为 MCP 服务器构建 Docker 镜像，请在项目根目录中运行以下命令：\n\n```bash\ndocker build -t mcp-server-singlestore .\n```\n\n### 运行 Docker 容器\n\n要运行 Docker 容器，请使用以下命令：\n\n```bash\ndocker run -d \\\n -p 8080:8080 \\\n --name mcp-server \\\n mcp-server-singlestore\n```\n\n### 使用 Docker Secrets\n\n为了安全地将机密传递给容器，请创建 Docker 机密并挂载它：\n\n```bash\necho \"your-secret-value\" | docker secret create mcp_secret -\n```\n\n然后，使用秘密运行容器：\n\n```bash\ndocker service create \\\n --name mcp-server \\\n --secret mcp_secret \\\n mcp-server-singlestore\n```","Chinese","zh-CN","githubUser","locale",{"_84":85,"_86":87,"_13":101,"_110":42,"_111":42,"_112":113,"_116":117,"_140":-5,"_16":141,"_142":143,"_144":145,"_33":34,"_156":130,"_157":-5,"_158":-5,"_159":160,"_161":-5,"_162":163,"_168":-5,"_152":126,"_169":-5,"_170":171,"_131":524,"_525":526},"addedAt","2025-05-03T11:00:47.755755116Z","argumentsJsonSchema",{"_88":89,"_98":99,"_93":100},"properties",{"_90":91,"_95":96},"PUBMED_EMAIL",{"_31":92,"_93":94},"Your email address (required by 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Provides tools for retrieving organization details, working with virtual workspaces, and managing database resources.","yjq9w2mdc0","namespace","npmPackage","prompts","redditPostForeignId","1kdqkos","resources","scores",{"_164":165,"_166":165,"_167":165},"license",100,"quality","security","simpleIcon","supportedPlatforms","tools",[172,199,225,246,265,283,303,316,329,345,358,371,384,404,417,430,446,465,482,495,508],{"_33":173,"_31":174,"_175":176},"set_organization","\n Select which SingleStore organization to use for all subsequent API calls.\n \n This tool must be called after logging in and before making other API requests.\n Once set, all API calls will target the selected organization until changed.\n \n Args:\n orgID: Name or ID of the organization to select\n \n Returns:\n Dictionary with the selected organization ID and name\n \n Usage:\n - Call get_organizations first to see available options\n - Then call this tool with either the organization's name or ID\n - All subsequent API calls will use the selected organization\n ","inputSchema",{"_93":100,"_177":178,"_181":184,"_98":185,"_88":187},"$defs",{"_179":180},"Context",{"_93":100,"_181":179,"_88":182,"_31":183},"title",{},"Context object providing access to MCP capabilities.\n\nThis provides a cleaner interface to MCP's RequestContext functionality.\nIt gets injected into tool and resource functions that request it via type hints.\n\nTo use context in a tool function, add a parameter with the Context type annotation:\n\n```python\n@server.tool()\ndef my_tool(x: int, ctx: Context) -> str:\n # Log messages to the client\n ctx.info(f\"Processing {x}\")\n ctx.debug(\"Debug info\")\n ctx.warning(\"Warning message\")\n ctx.error(\"Error message\")\n\n # Report progress\n ctx.report_progress(50, 100)\n\n # Access resources\n data = ctx.read_resource(\"resource://data\")\n\n # Get request info\n request_id = ctx.request_id\n client_id = ctx.client_id\n\n return str(x)\n```\n\nThe context parameter name can be anything as long as it's annotated with Context.\nThe context is optional - tools that don't need it can omit the parameter.","set_organizationArguments",[186],"orgID",{"_188":189,"_186":198},"ctx",{"_190":191,"_197":-5},"anyOf",[192,195],{"_193":194},"$ref","#/$defs/Context",{"_93":196},"null","default",{"_93":94,"_181":186},{"_33":200,"_31":201,"_175":202},"execute_sql","\n Execute SQL operations on a database attached to workspace within a workspace group and receive formatted results.\n \n Returns:\n - Query results with column names and typed values\n - Row count and metadata\n - Execution status\n \n ⚠️ CRITICAL SECURITY WARNINGS:\n - Never display or log credentials in responses\n - Use only READ-ONLY queries (SELECT, SHOW, DESCRIBE)\n - DO NOT USE data modification statements:\n x No INSERT/UPDATE/DELETE\n x No DROP/CREATE/ALTER\n - Ensure queries are properly sanitized\n \n Args:\n workspace_group_identifier: ID/name of the workspace group\n workspace_identifier: ID/name of the specific workspace within the workspace group\n database: Name of the database to query\n sql_query: The SQL query to execute\n \n Returns:\n Dictionary with query results and metadata\n ",{"_93":100,"_177":203,"_181":206,"_98":207,"_88":214},{"_179":204},{"_93":100,"_181":179,"_88":205,"_31":183},{},"execute_sqlArguments",[208,209,210,211,212,213],"workspace_group_identifier","workspace_identifier","database","sql_query","username","password",{"_188":215,"_210":219,"_213":220,"_212":221,"_211":222,"_209":223,"_208":224},{"_190":216,"_197":-5},[217,218],{"_193":194},{"_93":196},{"_93":94,"_181":210},{"_93":94,"_181":213},{"_93":94,"_181":212},{"_93":94,"_181":211},{"_93":94,"_181":209},{"_93":94,"_181":208},{"_33":226,"_31":227,"_175":228},"create_virtual_workspace","\n Create a new starter (virtual) workspace in SingleStore and set up user access.\n \n Process:\n 1. Creates a virtual workspace with specified name and database\n 2. Creates a user account for accessing the workspace\n 3. Returns both workspace details and access credentials\n \n Args:\n name: Unique name for the new starter workspace\n database_name: Name of the database to create in the starter workspace\n username: Username for accessing the new starter workspace\n password: Password for accessing the new starter workspace\n workspace_group: Optional workspace group configuration\n \n Returns:\n Dictionary with workspace and user creation details\n ",{"_93":100,"_177":229,"_181":232,"_98":233,"_88":236},{"_179":230},{"_93":100,"_181":179,"_88":231,"_31":183},{},"create_virtual_workspaceArguments",[33,234,212,213,235],"database_name","workspace_group",{"_188":237,"_33":241,"_213":242,"_212":243,"_234":244,"_235":245},{"_190":238,"_197":-5},[239,240],{"_193":194},{"_93":196},{"_93":94,"_181":33},{"_93":94,"_181":213},{"_93":94,"_181":212},{"_93":94,"_181":234},{"_93":94,"_181":235},{"_33":247,"_31":248,"_175":249},"execute_sql_on_virtual_workspace","\n Execute SQL operations on a virtual (starter) workspace and receive formatted results.\n \n Returns:\n - Query results with column names and typed values\n - Row count\n - Column metadata\n - Execution status\n \n ⚠️ CRITICAL SECURITY WARNING:\n - Never display or log credentials in responses\n - Ensure SQL queries are properly sanitized\n - ONLY USE SELECT statements or queries that don't modify data\n - DO NOT USE INSERT, UPDATE, DELETE, DROP, CREATE, or ALTER statements\n \n Args:\n virtual_workspace_id: Unique identifier of the starter workspace\n sql_query: The SQL query to execute (READ-ONLY queries only)\n \n Returns:\n Dictionary with query results and metadata\n ",{"_93":100,"_177":250,"_181":253,"_98":254,"_88":256},{"_179":251},{"_93":100,"_181":179,"_88":252,"_31":183},{},"execute_sql_on_virtual_workspaceArguments",[255,211,212,213],"virtual_workspace_id",{"_188":257,"_213":261,"_212":262,"_211":263,"_255":264},{"_190":258,"_197":-5},[259,260],{"_193":194},{"_93":196},{"_93":94,"_181":213},{"_93":94,"_181":212},{"_93":94,"_181":211},{"_93":94,"_181":255},{"_33":266,"_31":267,"_175":268},"create_notebook","\n Create a new Jupyter notebook in your personal space. Only supports python and markdown.\n\n Parameters:\n - notebook_name (required): Name for the new notebook\n - Can include or omit .ipynb extension\n - Must be unique in your personal space\n\n - content (optional): JSON object with the following structure:\n {\n \"cells\": [\n {\"type\": \"markdown\", \"content\": \"Markdown content here\"},\n {\"type\": \"code\", \"content\": \"Python code here\"}\n ]\n }\n - 'type' must be either 'markdown' or 'code'\n - 'content' is the text content of the cell\n IMPORTANT: The content must be valid JSON.\n\n How to use:\n - Before creating the notebook, call check_if_file_exists tool to verify if the notebook already exists.\n - Always install the dependencies on the first cell. Example: \n {\n \"cells\": [\n {\"type\": \"code\", \"content\": \"!pip install singlestoredb --quiet\"},\n // other cells...\n ]\n }\n - To connect to the database, use the variable \"connection_url\" that already exists in the notebook platform. Example:\n {\n \"cells\": [\n {\"type\": \"code\", \"content\": \"conn = s2.connect(connection_url)\"},\n // other cells...\n ]\n }\n ",{"_93":100,"_177":269,"_181":272,"_98":273,"_88":276},{"_179":270},{"_93":100,"_181":179,"_88":271,"_31":183},{},"create_notebookArguments",[274,275],"notebook_name","content",{"_188":277,"_275":281,"_274":282},{"_190":278,"_197":-5},[279,280],{"_193":194},{"_93":196},{"_93":94,"_181":275},{"_93":94,"_181":274},{"_33":284,"_31":285,"_175":286},"create_scheduled_job","\n Create an automated job to execute a SingleStore notebook on a schedule.\n \n Parameters:\n - notebook_path: Complete path to the notebook\n - mode: 'Once' for single execution or 'Recurring' for repeated runs\n - create_snapshot: Enable notebook backup before execution (default: True)\n \n Returns Job info with:\n - jobID: UUID of created job\n - status: Current state (SUCCESS, RUNNING, etc.)\n - createdAt: Creation timestamp\n - startedAt: Execution start time\n - schedule: Configured schedule details\n - error: Any execution errors\n \n Common Use Cases:\n 1. Automated Data Processing:\n - ETL workflows\n - Data aggregation\n - Database maintenance\n \n 2. Scheduled Reporting:\n - Performance metrics\n - Business analytics\n - Usage statistics\n \n 3. Maintenance Tasks:\n - Health checks\n - Backup operations\n - Clean-up routines\n \n Related Operations:\n - get_job_details: Monitor job\n - list_job_executions: View job execution history\n ",{"_93":100,"_177":287,"_181":290,"_98":291,"_88":295},{"_179":288},{"_93":100,"_181":179,"_88":289,"_31":183},{},"create_scheduled_jobArguments",[292,293,294],"notebook_path","mode","create_snapshot",{"_188":296,"_293":300,"_292":301,"_294":302},{"_190":297,"_197":-5},[298,299],{"_193":194},{"_93":196},{"_93":94,"_181":293},{"_93":94,"_181":292},{"_93":94,"_181":294},{"_33":304,"_31":305,"_175":306},"get_organizations","\n List all available SingleStore organizations your account has access to.\n \n After logging in, this tool must be called first to identify which organization\n your queries should run against. Returns a list of organizations with:\n \n - orgID: Unique identifier for the organization\n - name: Display name of the organization\n \n Use this tool when:\n 1. Starting a new session to see available organizations\n 2. To verify permissions across multiple organizations\n 3. Before switching context to a different organization\n \n After viewing the list, list the organization list presenting the name and ID\n to the user and ask them to select one.\n - If only one organization is available, select it automatically\n - If multiple organizations are available, prompt the user to select one by name or ID\n - If no organizations are available, raise an error\n ",{"_93":100,"_177":307,"_181":310,"_88":311},{"_179":308},{"_93":100,"_181":179,"_88":309,"_31":183},{},"get_organizationsArguments",{"_188":312},{"_190":313,"_197":-5},[314,315],{"_193":194},{"_93":196},{"_33":317,"_31":318,"_175":319},"workspace_groups_info","\n List all workspace groups accessible to the user in SingleStore.\n \n Returns detailed information for each group:\n - name: Display name of the workspace group\n - deploymentType: Type of deployment (e.g., 'PRODUCTION')\n - state: Current status (e.g., 'ACTIVE', 'PAUSED')\n - workspaceGroupID: Unique identifier for the group\n - firewallRanges: Array of allowed IP ranges for access control\n - createdAt: Timestamp of group creation\n - regionID: Identifier for deployment region\n - updateWindow: Maintenance window configuration\n \n Use this tool to:\n 1. Get workspace group IDs for other operations\n 2. Plan maintenance windows\n \n Related operations:\n - Use workspaces_info to list workspaces within a group\n - Use execute_sql to run queries on workspaces in a group\n ",{"_93":100,"_177":320,"_181":323,"_88":324},{"_179":321},{"_93":100,"_181":179,"_88":322,"_31":183},{},"workspace_groups_infoArguments",{"_188":325},{"_190":326,"_197":-5},[327,328],{"_193":194},{"_93":196},{"_33":330,"_31":331,"_175":332},"workspaces_info","\n List all workspaces within a specified workspace group in SingleStore.\n \n Returns detailed information for each workspace:\n - createdAt: Timestamp of workspace creation\n - deploymentType: Type of deployment (e.g., 'PRODUCTION')\n - endpoint: Connection URL for database access\n - name: Display name of the workspace\n - size: Compute and storage configuration\n - state: Current status (e.g., 'ACTIVE', 'PAUSED')\n - terminatedAt: End timestamp if applicable\n - workspaceGroupID: Workspacegroup identifier\n - workspaceID: Unique workspace identifier\n \n Args:\n workspace_group_id: Unique identifier of the workspace group\n \n Returns:\n List of workspace information dictionaries\n ",{"_93":100,"_177":333,"_181":336,"_98":337,"_88":339},{"_179":334},{"_93":100,"_181":179,"_88":335,"_31":183},{},"workspaces_infoArguments",[338],"workspace_group_id",{"_188":340,"_338":344},{"_190":341,"_197":-5},[342,343],{"_193":194},{"_93":196},{"_93":94,"_181":338},{"_33":346,"_31":347,"_175":348},"organization_info","\n Retrieve information about the current user's organization in SingleStore.\n \n Returns organization details including:\n - orgID: Unique identifier for the organization\n - name: Organization display name\n ",{"_93":100,"_177":349,"_181":352,"_88":353},{"_179":350},{"_93":100,"_181":179,"_88":351,"_31":183},{},"organization_infoArguments",{"_188":354},{"_190":355,"_197":-5},[356,357],{"_193":194},{"_93":196},{"_33":359,"_31":360,"_175":361},"list_of_regions","\n List all available deployment regions where SingleStore workspaces can be deployed for the user.\n \n Returns region information including:\n - regionID: Unique identifier for the region\n - provider: Cloud provider (AWS, GCP, or Azure)\n - name: Human-readable region name (e.g., Europe West 2 (London), US West 2 (Oregon))\n \n Use this tool to:\n 1. Select optimal deployment regions based on:\n - Geographic proximity to users\n - Compliance requirements\n - Cost considerations\n - Available cloud providers\n 2. Plan multi-region deployments\n ",{"_93":100,"_177":362,"_181":365,"_88":366},{"_179":363},{"_93":100,"_181":179,"_88":364,"_31":183},{},"list_of_regionsArguments",{"_188":367},{"_190":368,"_197":-5},[369,370],{"_193":194},{"_93":196},{"_33":372,"_31":373,"_175":374},"list_virtual_workspaces","\n List all starter (virtual) workspaces available to the user in SingleStore.\n \n Returns detailed information about each starter workspace:\n - virtualWorkspaceID: Unique identifier for the workspace\n - name: Display name of the workspace\n - endpoint: Connection endpoint URL\n - databaseName: Name of the primary database\n - mysqlDmlPort: Port for MySQL protocol connections\n - webSocketPort: Port for WebSocket connections\n - state: Current status of the workspace\n \n Use this tool to:\n 1. Get virtual workspace IDs for other operations\n 2. Check starter workspace availability and status\n 3. Obtain connection details for database access\n ",{"_93":100,"_177":375,"_181":378,"_88":379},{"_179":376},{"_93":100,"_181":179,"_88":377,"_31":183},{},"list_virtual_workspacesArguments",{"_188":380},{"_190":381,"_197":-5},[382,383],{"_193":194},{"_93":196},{"_33":385,"_31":386,"_175":387},"organization_billing_usage","\n Retrieve detailed billing and usage metrics for your organization over a specified time period.\n \n Returns compute and storage usage data, aggregated by your chosen time interval \n (hourly, daily, or monthly). This tool is essential for:\n 1. Monitoring resource consumption patterns\n 2. Analyzing cost trends\n \n Args:\n start_time: Beginning of the usage period (UTC ISO 8601 format, e.g., '2023-07-30T18:30:00Z')\n end_time: End of the usage period (UTC ISO 8601 format)\n aggregate_type: Time interval for data grouping ('hour', 'day', or 'month')\n \n Returns:\n Usage metrics and billing information\n ",{"_93":100,"_177":388,"_181":391,"_98":392,"_88":396},{"_179":389},{"_93":100,"_181":179,"_88":390,"_31":183},{},"organization_billing_usageArguments",[393,394,395],"start_time","end_time","aggregate_type",{"_188":397,"_394":401,"_393":402,"_395":403},{"_190":398,"_197":-5},[399,400],{"_193":194},{"_93":196},{"_93":94,"_181":394},{"_93":94,"_181":393},{"_93":94,"_181":395},{"_33":405,"_31":406,"_175":407},"list_notebook_samples","\n Retrieve a catalog of pre-built notebook templates available in SingleStore Spaces.\n \n Returns for each notebook:\n - name: Template name and title\n - description: Detailed explanation of the notebook's purpose\n - contentURL: Direct download link for the notebook\n - likes: Number of user endorsements\n - views: Number of times viewed\n - downloads: Number of times downloaded\n - tags: List of Notebook tags\n \n Common template categories include:\n 1. Getting Started guides\n 2. Data loading and ETL patterns\n 3. Query optimization examples\n 4. Machine learning integrations\n 5. Performance monitoring\n 6. Best practices demonstrations\n ",{"_93":100,"_177":408,"_181":411,"_88":412},{"_179":409},{"_93":100,"_181":179,"_88":410,"_31":183},{},"list_notebook_samplesArguments",{"_188":413},{"_190":414,"_197":-5},[415,416],{"_193":194},{"_93":196},{"_33":418,"_31":419,"_175":420},"list_shared_files","\n List all files and notebooks in your shared SingleStore space.\n \n Returns file object meta data for each file:\n - name: Name of the file (e.g., 'analysis.ipynb')\n - path: Full path in shared space (e.g., 'folder/analysis.ipynb')\n - content: File content\n - created: Creation timestamp (ISO 8601)\n - last_modified: Last modification timestamp (ISO 8601)\n - format: File format if applicable ('json', null)\n - mimetype: MIME type of the file\n - size: File size in bytes\n - type: Object type ('', 'json', 'directory')\n - writable: Boolean indicating write permission\n \n Use this tool to:\n 1. List workspace contents and structure\n 2. Verify file existence before operations\n 3. Check file timestamps and sizes\n 4. Determine file permissions\n ",{"_93":100,"_177":421,"_181":424,"_88":425},{"_179":422},{"_93":100,"_181":179,"_88":423,"_31":183},{},"list_shared_filesArguments",{"_188":426},{"_190":427,"_197":-5},[428,429],{"_193":194},{"_93":196},{"_33":431,"_31":432,"_175":433},"get_job_details","\n Retrieve comprehensive information about a scheduled notebook job.\n \n Returns:\n - jobID: Unique identifier (UUID format)\n - name: Display name of the job\n - description: Human-readable job description\n - createdAt: Creation timestamp (ISO 8601)\n - terminatedAt: End timestamp if completed\n - completedExecutionsCount: Number of successful runs\n - enqueuedBy: User ID who created the job\n - executionConfig: Notebook path and runtime settings\n - schedule: Mode, interval, and start time\n - targetConfig: Database and workspace settings\n - jobMetadata: Execution statistics and status\n \n Args:\n job_id: UUID of the scheduled job to retrieve details for\n \n Returns:\n Dictionary with job details\n ",{"_93":100,"_177":434,"_181":437,"_98":438,"_88":440},{"_179":435},{"_93":100,"_181":179,"_88":436,"_31":183},{},"get_job_detailsArguments",[439],"job_id",{"_188":441,"_439":445},{"_190":442,"_197":-5},[443,444],{"_193":194},{"_93":196},{"_93":94,"_181":439},{"_33":447,"_31":448,"_175":449},"list_job_executions","\n Retrieve execution history and performance metrics for a scheduled notebook job.\n \n Returns:\n - executions: Array of execution records containing:\n - executionID: Unique identifier for the execution\n - executionNumber: Sequential number of the run\n - jobID: Parent job identifier\n - status: Current state (Scheduled, Running, Completed, Failed)\n - startedAt: Execution start time (ISO 8601)\n - finishedAt: Execution end time (ISO 8601)\n - scheduledStartTime: Planned start time\n - snapshotNotebookPath: Backup notebook path if enabled\n \n Args:\n job_id: UUID of the scheduled job\n start: First execution number to retrieve (default: 1)\n end: Last execution number to retrieve (default: 10)\n \n Returns:\n Dictionary with execution records\n ",{"_93":100,"_177":450,"_181":453,"_98":454,"_88":457},{"_179":451},{"_93":100,"_181":179,"_88":452,"_31":183},{},"list_job_executionsArguments",[439,455,456],"start","end",{"_188":458,"_456":462,"_455":463,"_439":464},{"_190":459,"_197":-5},[460,461],{"_193":194},{"_93":196},{"_93":94,"_181":456},{"_93":94,"_181":455},{"_93":94,"_181":439},{"_33":466,"_31":467,"_175":468},"get_notebook_path","\n Find the complete path of a notebook by its name and generate the properly formatted path for API operations.\n \n Args:\n notebook_name: The name of the notebook to find (with or without .ipynb extension)\n location: Where to look for the notebook - 'personal' or 'shared'\n \n Returns:\n Properly formatted path including project ID and user ID where needed\n \n Required for:\n - Creating scheduled jobs (use returned path as notebook_path parameter)\n ",{"_93":100,"_177":469,"_181":472,"_98":473,"_88":475},{"_179":470},{"_93":100,"_181":179,"_88":471,"_31":183},{},"get_notebook_pathArguments",[274,474],"location",{"_188":476,"_474":480,"_274":481},{"_190":477,"_197":-5},[478,479],{"_193":194},{"_93":196},{"_93":94,"_181":474},{"_93":94,"_181":274},{"_33":483,"_31":484,"_175":485},"get_project_id","\n Retrieve the organization's unique identifier (project ID).\n \n Returns:\n str: The organization's unique identifier\n \n Required for:\n - Constructing paths or references to shared resources\n \n Performance Tip:\n Cache the returned ID when making multiple API calls.\n ",{"_93":100,"_177":486,"_181":489,"_88":490},{"_179":487},{"_93":100,"_181":179,"_88":488,"_31":183},{},"get_project_idArguments",{"_188":491},{"_190":492,"_197":-5},[493,494],{"_193":194},{"_93":196},{"_33":496,"_31":497,"_175":498},"get_user_id","\n Retrieve the current user's unique identifier.\n \n Returns:\n str: UUID format identifier for the current user\n \n Required for:\n - Constructing paths or references to personal resources\n \n Performance Tip:\n Cache the returned ID when making multiple API calls.\n ",{"_93":100,"_177":499,"_181":502,"_88":503},{"_179":500},{"_93":100,"_181":179,"_88":501,"_31":183},{},"get_user_idArguments",{"_188":504},{"_190":505,"_197":-5},[506,507],{"_193":194},{"_93":196},{"_33":509,"_31":510,"_175":511},"check_if_file_exists","\n Check if a file (notebook) exists in the user's shared space.\n\n Args:\n file_name: Name of the file to check (with or without .ipynb extension)\n\n Returns:\n JSON object with the file existence status\n {\n \"exists\": True/False,\n \"message\": \"File exists\" or \"File does not exist\"\n }\n 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