google-bigquery

Server path: /google-bigquery | Type: Application | PCID required: Yes

Tools

Tool	Description
`google-bigquery_list_all_accessible_projects`	List all accessible Google Cloud projects with BigQuery enabled. Returns project IDs and names.
`google-bigquery_execute_sql_query`	Execute a SQL query on BigQuery and return results. Supports Standard SQL (recommended) and Legacy SQL. Can execute SELECT, INSERT, UPDATE, DELETE, CREATE, DROP, and other SQL statements.
`google-bigquery_list_datasets_in_project`	List all datasets in a project. Returns dataset IDs, locations, and creation times.
`google-bigquery_get_dataset_metadata`	Get detailed metadata about a dataset: location, creation time, description, and labels.
`google-bigquery_create_new_dataset`	Create a new dataset in BigQuery. Location cannot be changed after creation and must match query location.
`google-bigquery_delete_dataset_permanently`	Permanently delete a dataset. WARNING: Irreversible. Fails if dataset contains tables unless deleteContents=true.
`google-bigquery_list_tables_in_dataset`	List all tables and views in a dataset. Returns table IDs, types, creation times, and row counts.
`google-bigquery_get_table_schema_and_metadata`	Get table information: schema (columns, types, modes), row count, size, creation time, and last modified time.
`google-bigquery_create_table_with_schema`	Create a new empty table with defined schema. Define columns with types (STRING, INTEGER, FLOAT, BOOLEAN, TIMESTAMP, DATE, etc) and modes (NULLABLE, REQUIRED, REPEATED).
`google-bigquery_delete_table_permanently`	Permanently delete a table. WARNING: Irreversible. All data will be lost. No recovery option.
`google-bigquery_insert_rows_into_table`	Insert rows into a table. Each row object must match table schema column names and types. Data immediately available for querying.
`google-bigquery_query_table_data_simple`	Fetch rows from a table (SELECT * LIMIT n). For complex queries with WHERE, JOIN, GROUP BY, use execute_sql_query instead.
`google-bigquery_get_query_job_status`	Get job information: status (PENDING, RUNNING, DONE), statistics (bytes processed, rows), and errors if failed.
`google-bigquery_list_recent_query_jobs`	List recent jobs in a project. Returns job IDs, status, configuration, and timing. Useful for monitoring and debugging.

google-bigquery_list_all_accessible_projects

List all accessible Google Cloud projects with BigQuery enabled. Returns project IDs and names.

Show inputSchema

{
  "type": "object",
  "properties": {
    "PCID": {
      "type": "string",
      "description": "Pink Connect ID for Google BigQuery connection"
    }
  },
  "required": [
    "PCID"
  ]
}

google-bigquery_execute_sql_query

Execute a SQL query on BigQuery and return results. Supports Standard SQL (recommended) and Legacy SQL. Can execute SELECT, INSERT, UPDATE, DELETE, CREATE, DROP, and other SQL statements. Parameters:

Parameter	Type	Required	Default	Description
`projectId`	string	Yes	—	Project ID where query will run. Use list_all_accessible_projects to find available projects.
`query`	string	Yes	—	SQL query to execute. Standard SQL example: SELECT * FROM `project.dataset.table` LIMIT 10
`useLegacySql`	boolean	No	`false`	Use Legacy SQL syntax. Default: false (Standard SQL recommended).
`maxResults`	number	No	—	Maximum rows to return. Must be a positive number. Limits large result sets.
`location`	string	No	`"US"`	Geographic location for query (US, EU, asia-northeast1, etc). Must match dataset location. Default: US

Show inputSchema

{
  "type": "object",
  "properties": {
    "PCID": {
      "type": "string",
      "description": "Pink Connect ID for Google BigQuery connection"
    },
    "projectId": {
      "type": "string",
      "description": "Project ID where query will run. Use list_all_accessible_projects to find available projects."
    },
    "query": {
      "type": "string",
      "description": "SQL query to execute. Standard SQL example: SELECT * FROM `project.dataset.table` LIMIT 10"
    },
    "useLegacySql": {
      "type": "boolean",
      "default": false,
      "description": "Use Legacy SQL syntax. Default: false (Standard SQL recommended)."
    },
    "maxResults": {
      "type": "number",
      "description": "Maximum rows to return. Must be a positive number. Limits large result sets."
    },
    "location": {
      "type": "string",
      "default": "US",
      "description": "Geographic location for query (US, EU, asia-northeast1, etc). Must match dataset location. Default: US"
    }
  },
  "required": [
    "PCID",
    "projectId",
    "query"
  ]
}

google-bigquery_list_datasets_in_project

List all datasets in a project. Returns dataset IDs, locations, and creation times. Parameters:

Parameter	Type	Required	Default	Description
`projectId`	string	Yes	—	Project ID to list datasets from

Show inputSchema

{
  "type": "object",
  "properties": {
    "PCID": {
      "type": "string",
      "description": "Pink Connect ID for Google BigQuery connection"
    },
    "projectId": {
      "type": "string",
      "description": "Project ID to list datasets from"
    }
  },
  "required": [
    "PCID",
    "projectId"
  ]
}

google-bigquery_get_dataset_metadata

Get detailed metadata about a dataset: location, creation time, description, and labels. Parameters:

Parameter	Type	Required	Default	Description
`projectId`	string	Yes	—	Project ID containing the dataset
`datasetId`	string	Yes	—	Dataset ID to get information about

Show inputSchema

{
  "type": "object",
  "properties": {
    "PCID": {
      "type": "string",
      "description": "Pink Connect ID for Google BigQuery connection"
    },
    "projectId": {
      "type": "string",
      "description": "Project ID containing the dataset"
    },
    "datasetId": {
      "type": "string",
      "description": "Dataset ID to get information about"
    }
  },
  "required": [
    "PCID",
    "projectId",
    "datasetId"
  ]
}

google-bigquery_create_new_dataset

Create a new dataset in BigQuery. Location cannot be changed after creation and must match query location. Parameters:

Parameter	Type	Required	Default	Description
`projectId`	string	Yes	—	Project ID where dataset will be created
`datasetId`	string	Yes	—	Dataset name. Must start with letter or underscore, then letters, numbers, and underscores. Max 1024 chars.
`location`	string	No	`"US"`	Geographic location (US, EU, asia-northeast1, etc). Cannot be changed later. Default: US
`description`	string	No	—	Optional dataset description

Show inputSchema

{
  "type": "object",
  "properties": {
    "PCID": {
      "type": "string",
      "description": "Pink Connect ID for Google BigQuery connection"
    },
    "projectId": {
      "type": "string",
      "description": "Project ID where dataset will be created"
    },
    "datasetId": {
      "type": "string",
      "description": "Dataset name. Must start with letter or underscore, then letters, numbers, and underscores. Max 1024 chars."
    },
    "location": {
      "type": "string",
      "default": "US",
      "description": "Geographic location (US, EU, asia-northeast1, etc). Cannot be changed later. Default: US"
    },
    "description": {
      "type": "string",
      "description": "Optional dataset description"
    }
  },
  "required": [
    "PCID",
    "projectId",
    "datasetId"
  ]
}

google-bigquery_delete_dataset_permanently

Permanently delete a dataset. WARNING: Irreversible. Fails if dataset contains tables unless deleteContents=true. Parameters:

Parameter	Type	Required	Default	Description
`projectId`	string	Yes	—	Project ID containing the dataset
`datasetId`	string	Yes	—	Dataset ID to delete
`deleteContents`	boolean	No	`false`	Delete all tables in dataset. Default: false (fails if tables exist). Use with caution.

Show inputSchema

{
  "type": "object",
  "properties": {
    "PCID": {
      "type": "string",
      "description": "Pink Connect ID for Google BigQuery connection"
    },
    "projectId": {
      "type": "string",
      "description": "Project ID containing the dataset"
    },
    "datasetId": {
      "type": "string",
      "description": "Dataset ID to delete"
    },
    "deleteContents": {
      "type": "boolean",
      "default": false,
      "description": "Delete all tables in dataset. Default: false (fails if tables exist). Use with caution."
    }
  },
  "required": [
    "PCID",
    "projectId",
    "datasetId"
  ]
}

google-bigquery_list_tables_in_dataset

List all tables and views in a dataset. Returns table IDs, types, creation times, and row counts. Parameters:

Parameter	Type	Required	Default	Description
`projectId`	string	Yes	—	Project ID containing the dataset
`datasetId`	string	Yes	—	Dataset ID to list tables from

Show inputSchema

{
  "type": "object",
  "properties": {
    "PCID": {
      "type": "string",
      "description": "Pink Connect ID for Google BigQuery connection"
    },
    "projectId": {
      "type": "string",
      "description": "Project ID containing the dataset"
    },
    "datasetId": {
      "type": "string",
      "description": "Dataset ID to list tables from"
    }
  },
  "required": [
    "PCID",
    "projectId",
    "datasetId"
  ]
}

google-bigquery_get_table_schema_and_metadata

Get table information: schema (columns, types, modes), row count, size, creation time, and last modified time. Parameters:

Parameter	Type	Required	Default	Description
`projectId`	string	Yes	—	Project ID containing the table
`datasetId`	string	Yes	—	Dataset ID containing the table
`tableId`	string	Yes	—	Table ID to get information about

Show inputSchema

{
  "type": "object",
  "properties": {
    "PCID": {
      "type": "string",
      "description": "Pink Connect ID for Google BigQuery connection"
    },
    "projectId": {
      "type": "string",
      "description": "Project ID containing the table"
    },
    "datasetId": {
      "type": "string",
      "description": "Dataset ID containing the table"
    },
    "tableId": {
      "type": "string",
      "description": "Table ID to get information about"
    }
  },
  "required": [
    "PCID",
    "projectId",
    "datasetId",
    "tableId"
  ]
}

google-bigquery_create_table_with_schema

Create a new empty table with defined schema. Define columns with types (STRING, INTEGER, FLOAT, BOOLEAN, TIMESTAMP, DATE, etc) and modes (NULLABLE, REQUIRED, REPEATED). Parameters:

Parameter	Type	Required	Default	Description
`projectId`	string	Yes	—	Project ID where table will be created
`datasetId`	string	Yes	—	Dataset ID where table will be created. Dataset must exist.
`tableId`	string	Yes	—	Table name. Must start with letter or underscore, then letters, numbers, and underscores. Max 1024 chars.
`schema`	object[]	Yes	—	Array of column definitions. At least one column required.
`description`	string	No	—	Optional table description

Show inputSchema

{
  "type": "object",
  "properties": {
    "PCID": {
      "type": "string",
      "description": "Pink Connect ID for Google BigQuery connection"
    },
    "projectId": {
      "type": "string",
      "description": "Project ID where table will be created"
    },
    "datasetId": {
      "type": "string",
      "description": "Dataset ID where table will be created. Dataset must exist."
    },
    "tableId": {
      "type": "string",
      "description": "Table name. Must start with letter or underscore, then letters, numbers, and underscores. Max 1024 chars."
    },
    "schema": {
      "type": "array",
      "items": {
        "type": "object",
        "properties": {
          "name": {
            "type": "string",
            "description": "Column name. Must be unique."
          },
          "type": {
            "type": "string",
            "description": "Column type: STRING, INTEGER, FLOAT, BOOLEAN, TIMESTAMP, DATE, DATETIME, TIME, BYTES, NUMERIC, BIGNUMERIC, GEOGRAPHY, RECORD"
          },
          "mode": {
            "type": "string",
            "description": "NULLABLE (default), REQUIRED, or REPEATED"
          }
        }
      },
      "description": "Array of column definitions. At least one column required."
    },
    "description": {
      "type": "string",
      "description": "Optional table description"
    }
  },
  "required": [
    "PCID",
    "projectId",
    "datasetId",
    "tableId",
    "schema"
  ]
}

google-bigquery_delete_table_permanently

Permanently delete a table. WARNING: Irreversible. All data will be lost. No recovery option. Parameters:

Parameter	Type	Required	Default	Description
`projectId`	string	Yes	—	Project ID containing the table
`datasetId`	string	Yes	—	Dataset ID containing the table
`tableId`	string	Yes	—	Table ID to delete

Show inputSchema

{
  "type": "object",
  "properties": {
    "PCID": {
      "type": "string",
      "description": "Pink Connect ID for Google BigQuery connection"
    },
    "projectId": {
      "type": "string",
      "description": "Project ID containing the table"
    },
    "datasetId": {
      "type": "string",
      "description": "Dataset ID containing the table"
    },
    "tableId": {
      "type": "string",
      "description": "Table ID to delete"
    }
  },
  "required": [
    "PCID",
    "projectId",
    "datasetId",
    "tableId"
  ]
}

google-bigquery_insert_rows_into_table

Insert rows into a table. Each row object must match table schema column names and types. Data immediately available for querying. Parameters:

Parameter	Type	Required	Default	Description
`projectId`	string	Yes	—	Project ID containing the table
`datasetId`	string	Yes	—	Dataset ID containing the table
`tableId`	string	Yes	—	Table ID to insert into. Table must exist with matching schema.
`rows`	object[]	Yes	—	Array of row objects. Keys must match column names. Example: [{name: “John”, age: 30}]

Show inputSchema

{
  "type": "object",
  "properties": {
    "PCID": {
      "type": "string",
      "description": "Pink Connect ID for Google BigQuery connection"
    },
    "projectId": {
      "type": "string",
      "description": "Project ID containing the table"
    },
    "datasetId": {
      "type": "string",
      "description": "Dataset ID containing the table"
    },
    "tableId": {
      "type": "string",
      "description": "Table ID to insert into. Table must exist with matching schema."
    },
    "rows": {
      "type": "array",
      "items": {
        "type": "object",
        "additionalProperties": true
      },
      "description": "Array of row objects. Keys must match column names. Example: [{name: \"John\", age: 30}]"
    }
  },
  "required": [
    "PCID",
    "projectId",
    "datasetId",
    "tableId",
    "rows"
  ]
}

google-bigquery_query_table_data_simple

Fetch rows from a table (SELECT * LIMIT n). For complex queries with WHERE, JOIN, GROUP BY, use execute_sql_query instead. Parameters:

Parameter	Type	Required	Default	Description
`projectId`	string	Yes	—	Project ID containing the table
`datasetId`	string	Yes	—	Dataset ID containing the table
`tableId`	string	Yes	—	Table ID to query
`maxResults`	number	No	`100`	Maximum rows to return. Must be a positive number. Default: 100

Show inputSchema

{
  "type": "object",
  "properties": {
    "PCID": {
      "type": "string",
      "description": "Pink Connect ID for Google BigQuery connection"
    },
    "projectId": {
      "type": "string",
      "description": "Project ID containing the table"
    },
    "datasetId": {
      "type": "string",
      "description": "Dataset ID containing the table"
    },
    "tableId": {
      "type": "string",
      "description": "Table ID to query"
    },
    "maxResults": {
      "type": "number",
      "default": 100,
      "description": "Maximum rows to return. Must be a positive number. Default: 100"
    }
  },
  "required": [
    "PCID",
    "projectId",
    "datasetId",
    "tableId"
  ]
}

google-bigquery_get_query_job_status

Get job information: status (PENDING, RUNNING, DONE), statistics (bytes processed, rows), and errors if failed. Parameters:

Parameter	Type	Required	Default	Description
`projectId`	string	Yes	—	Project ID where job was executed
`jobId`	string	Yes	—	Job ID returned from execute_sql_query

Show inputSchema

{
  "type": "object",
  "properties": {
    "PCID": {
      "type": "string",
      "description": "Pink Connect ID for Google BigQuery connection"
    },
    "projectId": {
      "type": "string",
      "description": "Project ID where job was executed"
    },
    "jobId": {
      "type": "string",
      "description": "Job ID returned from execute_sql_query"
    }
  },
  "required": [
    "PCID",
    "projectId",
    "jobId"
  ]
}

google-bigquery_list_recent_query_jobs

List recent jobs in a project. Returns job IDs, status, configuration, and timing. Useful for monitoring and debugging. Parameters:

Parameter	Type	Required	Default	Description
`projectId`	string	Yes	—	Project ID to list jobs from
`maxResults`	number	No	`100`	Maximum jobs to return. Must be a positive number. Default: 100
`allUsers`	boolean	No	`false`	Show jobs from all users. Default: false (only your jobs). Requires permissions.

Show inputSchema

{
  "type": "object",
  "properties": {
    "PCID": {
      "type": "string",
      "description": "Pink Connect ID for Google BigQuery connection"
    },
    "projectId": {
      "type": "string",
      "description": "Project ID to list jobs from"
    },
    "maxResults": {
      "type": "number",
      "default": 100,
      "description": "Maximum jobs to return. Must be a positive number. Default: 100"
    },
    "allUsers": {
      "type": "boolean",
      "default": false,
      "description": "Show jobs from all users. Default: false (only your jobs). Requires permissions."
    }
  },
  "required": [
    "PCID",
    "projectId"
  ]
}

Triggers API

Platform API

Embedded MCP Servers

Application MCP Servers

Skills Guides

Tools

google-bigquery_list_all_accessible_projects

google-bigquery_execute_sql_query

google-bigquery_list_datasets_in_project

google-bigquery_get_dataset_metadata

google-bigquery_create_new_dataset

google-bigquery_delete_dataset_permanently

google-bigquery_list_tables_in_dataset

google-bigquery_get_table_schema_and_metadata

google-bigquery_create_table_with_schema

google-bigquery_delete_table_permanently

google-bigquery_insert_rows_into_table

google-bigquery_query_table_data_simple

google-bigquery_get_query_job_status

google-bigquery_list_recent_query_jobs

Triggers API

Platform API

Embedded MCP Servers

Application MCP Servers

Skills Guides

Documentation Index

​Tools

​google-bigquery_list_all_accessible_projects

​google-bigquery_execute_sql_query

​google-bigquery_list_datasets_in_project

​google-bigquery_get_dataset_metadata

​google-bigquery_create_new_dataset

​google-bigquery_delete_dataset_permanently

​google-bigquery_list_tables_in_dataset

​google-bigquery_get_table_schema_and_metadata

​google-bigquery_create_table_with_schema

​google-bigquery_delete_table_permanently

​google-bigquery_insert_rows_into_table

​google-bigquery_query_table_data_simple

​google-bigquery_get_query_job_status

​google-bigquery_list_recent_query_jobs

Tools

google-bigquery_list_all_accessible_projects

google-bigquery_execute_sql_query

google-bigquery_list_datasets_in_project

google-bigquery_get_dataset_metadata

google-bigquery_create_new_dataset

google-bigquery_delete_dataset_permanently

google-bigquery_list_tables_in_dataset

google-bigquery_get_table_schema_and_metadata

google-bigquery_create_table_with_schema

google-bigquery_delete_table_permanently

google-bigquery_insert_rows_into_table

google-bigquery_query_table_data_simple

google-bigquery_get_query_job_status

google-bigquery_list_recent_query_jobs