Google BigQuery
Run SQL queries on BigQuery datasets, list tables, and inspect schemas.
От сообщества: Добавлен пользователем или импортирован; проверьте владельца перед подключениемРаботаетБез входаГлобальныйБесплатноТолько чтение
Что умеет
- List Dataset Ids: List BigQuery dataset IDs in a Google Cloud project.
- Get Dataset Info: Get metadata information about a BigQuery dataset.
- List Table Ids: List table ids in a BigQuery dataset.
Какие данные видит
Нужен ли аккаунт
Не нужен: сервер работает без входа
Run SQL queries on BigQuery datasets, list tables, and inspect schemas. Manage jobs, export results, and explore data warehouse resources.
Список инструментов сервера (5)
Технические названия из tools/list. Нужны только разработчикам.
| list_dataset_ids | List BigQuery dataset IDs in a Google Cloud project. |
| get_dataset_info | Get metadata information about a BigQuery dataset. |
| list_table_ids | List table ids in a BigQuery dataset. |
| get_table_info | Get metadata information about a BigQuery table. |
| execute_sql | Run a SQL query in the project and return the result. This tool is restricted to only `SELECT` statements. `INSERT`, `UPDATE`, and `DELETE` statements and stored procedures aren't allowed. If the query doesn't include a `SELECT` statement, an error is returned. For information on creating queries, see the [GoogleSQL documentation](https://cloud.google.com/bigquery/docs/reference/standard-sql/query-syntax). The `execute_sql` tool can also have side effects if the the query invokes [remote functions](https://cloud.google.com/bigquery/docs/remote-functions) or [Python UDFs](https://cloud.google.com/bigquery/docs/user-defined-functions-python). All queries that are run using the `execute_sql` tool have a label that identifies the tool as the source. You can use this label to filter the queries using the label and value pair `goog-mcp-server: true`. Queries are charged to the project specified in the `project_id` field. Example Queries: -- Count the number of penguins in each island. SELECT island, COUNT(*) AS population FROM bigquery-public-data.ml_datasets.penguins GROUP BY island -- Evaluate a bigquery ML Model. SELECT * FROM ML.EVALUATE(MODEL `my_dataset.my_model`) -- Evaluate BigQuery ML model on custom data SELECT * FROM ML.EVALUATE(MODEL `my_dataset.my_model`, (SELECT * FROM `my_dataset.my_table`)) -- Predict using BigQuery ML model: SELECT * FROM ML.PREDICT(MODEL `my_dataset.my_model`, (SELECT * FROM `my_dataset.my_table`)) -- Forecast data using AI.FORECAST SELECT * FROM AI.FORECAST(TABLE `project.dataset.my_table`, data_col => 'num_trips', timestamp_col => 'date', id_cols => ['usertype'], horizon => 30) |