BigQuery (Service Account)

What you can do

Connect this agent connector to let your agent:

• Run run — Execute a SQL query synchronously against BigQuery and return results immediately
• List list — List all tables and views in a BigQuery dataset
• Get get — Retrieve metadata and schema for a specific BigQuery table or view, including column names, types, descriptions, and table properties

Authentication

This connector uses Service Account authentication.

Set up the connector

In Scalekit dashboard, go to Agent Auth → Create Connection. Find BigQuery (Service Account) and click Create.

That’s it — no OAuth credentials or redirect URIs needed. BigQuery Service Account uses server-to-server authentication handled entirely through your GCP service account credentials.

Code examples

Connect to BigQuery using a GCP service account — Scalekit handles authentication automatically using your service account credentials.

Node.js

import { ScalekitClient } from '@scalekit-sdk/node';
import 'dotenv/config';

const connectionName = 'bigqueryserviceaccount'; // get your connection name from connection configurations
const identifier = 'user_123';                   // your unique user identifier

// Get your credentials from app.scalekit.com → Developers → Settings → API Credentials
const scalekit = new ScalekitClient(
  process.env.SCALEKIT_ENV_URL,
  process.env.SCALEKIT_CLIENT_ID,
  process.env.SCALEKIT_CLIENT_SECRET
);
const actions = scalekit.actions;

// Create a connected account with your service account credentials
await actions.getOrCreateConnectedAccount({
  connectionName,
  identifier,
  authorizationDetails: {
    staticAuth: {
      serviceAccountJson: '<paste your GCP service account JSON here>',
    },
  },
});

// Execute a BigQuery tool
const result = await actions.executeTool({
  toolName: 'bigqueryserviceaccount_run_query',
  connectionName,
  identifier,
  toolInput: {
    query: 'SELECT 1 AS test',
  },
});
console.log(result);

Python

import scalekit.client
import os
from dotenv import load_dotenv

# Load environment variables
load_dotenv()

scalekit = scalekit.client.ScalekitClient(
    os.getenv("SCALEKIT_ENV_URL"),
    os.getenv("SCALEKIT_CLIENT_ID"),
    os.getenv("SCALEKIT_CLIENT_SECRET")
)
actions = scalekit.actions

CONNECTOR  = "bigqueryserviceaccount"
IDENTIFIER = "user_123"

# Service account JSON (replace with a real one)
SERVICE_ACCOUNT_JSON = """{
  "type": "service_account",
  "project_id": "my-gcp-project",
  "private_key_id": "key-id",
  "private_key": "-----BEGIN PRIVATE KEY-----\\nREPLACE_WITH_REAL_PRIVATE_KEY\\n-----END PRIVATE KEY-----\\n",
  "client_email": "my-sa@my-gcp-project.iam.gserviceaccount.com",
  "client_id": "123456789",
  "auth_uri": "https://accounts.google.com/o/oauth2/auth",
  "token_uri": "https://oauth2.googleapis.com/token",
  "auth_provider_x509_cert_url": "https://www.googleapis.com/oauth2/v1/certs",
  "client_x509_cert_url": "https://www.googleapis.com/robot/v1/metadata/x509/my-sa%40my-gcp-project.iam.gserviceaccount.com",
  "universe_domain": "googleapis.com"
}"""

# Step 1: Get or create connected account with service account credentials
response = actions.get_or_create_connected_account(
    connection_name=CONNECTOR,
    identifier=IDENTIFIER,
    authorization_details={
        "static_auth": {
            "service_account_json": SERVICE_ACCOUNT_JSON
        }
    }
)

account = response.connected_account
print(f"Connected account: {account.id} | Status: {account.status}")

# Step 2: Execute a BigQuery tool
result = actions.execute_tool(
    tool_name="bigqueryserviceaccount_run_query",
    connection_name=CONNECTOR,
    identifier=IDENTIFIER,
    tool_input={
        "query": "SELECT 1 AS test"
    }
)

print("Query result:", result.data)

Proxy API Calls

Note

Scalekit automatically resolves the GCP project ID in the base URL from the connected service account credentials. You only need to provide the path relative to the project, e.g. /datasets or /datasets/{datasetId}/tables.

Node.js

// Make a direct BigQuery REST API call via Scalekit proxy
// Base URL is already scoped to: .../bigquery/v2/projects/{project_id}
const result = await actions.request({
  connectionName,
  identifier,
  path: '/datasets',
  method: 'GET',
});
console.log(result);

Python

# Make a direct BigQuery REST API call via Scalekit proxy
# Base URL is already scoped to: .../bigquery/v2/projects/{project_id}
result = actions.request(
    connection_name=CONNECTOR,
    identifier=IDENTIFIER,
    path="/datasets",
    method="GET"
)
print(result)

Tool list

bigqueryserviceaccount_get_dataset Retrieve metadata for a specific BigQuery dataset, including location, description, labels, access controls, and creation/modification times. 1 param ▾

Retrieve metadata for a specific BigQuery dataset, including location, description, labels, access controls, and creation/modification times.

Name Type Required Description

dataset_id string required The ID of the dataset to retrieve

bigqueryserviceaccount_get_job Retrieve the status and configuration of a BigQuery job by its job ID. Use this to poll for completion of an async query job submitted via Insert Query Job. 2 params ▾

Retrieve the status and configuration of a BigQuery job by its job ID. Use this to poll for completion of an async query job submitted via Insert Query Job.

Name Type Required Description

job_id string required The ID of the job to retrieve

location string optional Geographic location where the job was created, e.g. US or EU

bigqueryserviceaccount_get_model Retrieve metadata for a specific BigQuery ML model, including model type, feature columns, label columns, and training run details. 2 params ▾

Retrieve metadata for a specific BigQuery ML model, including model type, feature columns, label columns, and training run details.

Name Type Required Description

dataset_id string required The ID of the dataset containing the model

model_id string required The ID of the model to retrieve

bigqueryserviceaccount_get_query_results Retrieve the results of a completed BigQuery query job. Supports pagination via page tokens. Use after polling Get Job until status is DONE. 5 params ▾

Retrieve the results of a completed BigQuery query job. Supports pagination via page tokens. Use after polling Get Job until status is DONE.

Name Type Required Description

job_id string required The ID of the completed query job

location string optional Geographic location where the job was created, e.g. US or EU

max_results integer optional Maximum number of rows to return per page

page_token string optional Page token from a previous response to retrieve the next page of results

timeout_ms integer optional Maximum milliseconds to wait if the query has not yet completed

bigqueryserviceaccount_get_routine Retrieve the definition and metadata of a specific BigQuery routine (stored procedure or UDF), including its arguments, return type, and body. 2 params ▾

Retrieve the definition and metadata of a specific BigQuery routine (stored procedure or UDF), including its arguments, return type, and body.

Name Type Required Description

dataset_id string required The ID of the dataset containing the routine

routine_id string required The ID of the routine to retrieve

bigqueryserviceaccount_get_table Retrieve metadata and schema for a specific BigQuery table or view, including column names, types, descriptions, and table properties. 2 params ▾

Retrieve metadata and schema for a specific BigQuery table or view, including column names, types, descriptions, and table properties.

Name Type Required Description

dataset_id string required The ID of the dataset containing the table

table_id string required The ID of the table or view to retrieve

bigqueryserviceaccount_list_datasets List all BigQuery datasets in the project. Supports filtering by label and pagination. 4 params ▾

List all BigQuery datasets in the project. Supports filtering by label and pagination.

Name Type Required Description

all boolean optional If true, includes hidden datasets in the results

filter string optional Label filter expression to restrict results, e.g. labels.env:prod

max_results integer optional Maximum number of datasets to return per page

page_token string optional Page token from a previous response to retrieve the next page

bigqueryserviceaccount_list_jobs List BigQuery jobs in the project. Supports filtering by state and projection, and pagination. 5 params ▾

List BigQuery jobs in the project. Supports filtering by state and projection, and pagination.

Name Type Required Description

all_users boolean optional If true, returns jobs for all users in the project; otherwise returns only the current user's jobs

max_results integer optional Maximum number of jobs to return per page

page_token string optional Page token from a previous response to retrieve the next page

projection string optional Controls the fields returned: minimal (default) or full

state_filter string optional Filter jobs by state: done, pending, or running

bigqueryserviceaccount_list_models List all BigQuery ML models in a dataset, including their model type, training status, and creation time. 3 params ▾

List all BigQuery ML models in a dataset, including their model type, training status, and creation time.

Name Type Required Description

dataset_id string required The ID of the dataset to list models from

max_results integer optional Maximum number of models to return per page

page_token string optional Page token from a previous response to retrieve the next page

bigqueryserviceaccount_list_routines List all stored procedures and user-defined functions (UDFs) in a BigQuery dataset. 4 params ▾

List all stored procedures and user-defined functions (UDFs) in a BigQuery dataset.

Name Type Required Description

dataset_id string required The ID of the dataset to list routines from

filter string optional Filter expression to restrict results, e.g. routineType:SCALAR_FUNCTION

max_results integer optional Maximum number of routines to return per page

page_token string optional Page token from a previous response to retrieve the next page

bigqueryserviceaccount_list_table_data Read rows directly from a BigQuery table without writing a SQL query. Supports pagination, row offset, and field selection. 6 params ▾

Read rows directly from a BigQuery table without writing a SQL query. Supports pagination, row offset, and field selection.

Name Type Required Description

dataset_id string required The ID of the dataset containing the table

table_id string required The ID of the table to read rows from

max_results integer optional Maximum number of rows to return per page

page_token string optional Page token from a previous response to retrieve the next page

selected_fields string optional Comma-separated list of fields to return; if omitted all fields are returned

start_index integer optional Zero-based row index to start reading from

bigqueryserviceaccount_list_tables List all tables and views in a BigQuery dataset. Supports pagination. 3 params ▾

List all tables and views in a BigQuery dataset. Supports pagination.

Name Type Required Description

dataset_id string required The ID of the dataset to list tables from

max_results integer optional Maximum number of tables to return per page

page_token string optional Page token from a previous response to retrieve the next page

bigqueryserviceaccount_run_query Execute a SQL query synchronously against BigQuery and return results immediately. Best for short-running queries. For long-running queries use Insert Query Job instead. 7 params ▾

Execute a SQL query synchronously against BigQuery and return results immediately. Best for short-running queries. For long-running queries use Insert Query Job instead.

Name Type Required Description

query string required SQL query to execute

create_session boolean optional If true, creates a new session and returns a session ID in the response

dry_run boolean optional If true, validates the query and returns estimated bytes processed without executing

location string optional Geographic location of the dataset, e.g. US or EU

max_results integer optional Maximum number of rows to return in the response

timeout_ms integer optional Maximum milliseconds to wait for query completion before returning

use_legacy_sql boolean optional Use BigQuery legacy SQL syntax instead of standard SQL