Google BigQuery

Authentication

This connector uses OAuth 2.0. Scalekit acts as the OAuth client: it redirects your user to Google BigQuery, obtains an access token, and automatically refreshes it before it expires. Your agent code never handles tokens directly — you only pass a connectionName and a user identifier.

You supply your Google BigQuery Connected App credentials (Client ID + Secret) once per environment in the Scalekit dashboard.

Set up the connector

Register your Scalekit environment with the Google BigQuery connector so Scalekit handles the authentication flow and token lifecycle for you. The connection name you create will be used to identify and invoke the connection programmatically. Then complete the configuration in your application as follows:

Caution

Google applications using scopes that permit access to certain user data must complete a verification process.

1. Set up auth redirects

   • In Scalekit dashboard, go to Agent Auth → Create Connection. Find Google BigQuery and click Create. Click Use your own credentials and copy the redirect URI. It looks like https://<SCALEKIT_ENVIRONMENT_URL>/sso/v1/oauth/<CONNECTION_ID>/callback.

     

   • Navigate to Google Cloud Console → APIs & Services → Credentials. Select + Create Credentials, then OAuth client ID. Choose Web application from the Application type menu.

     

   • Under Authorized redirect URIs, click + Add URI, paste the redirect URI, and click Create.

     

2. Enable the BigQuery API

   • In Google Cloud Console, go to APIs & Services → Library. Search for “BigQuery API” and click Enable.

     

3. Get client credentials

   • Google provides your Client ID and Client Secret after you create the OAuth client ID in step 1.

4. Add credentials in Scalekit

   • In Scalekit dashboard, go to Agent Auth → Connections and open the connection you created.

   • Enter your credentials:

     • Client ID (from above)
     • Client Secret (from above)
     • Permissions (scopes — see Google API Scopes reference)

     

   • Click Save.

Code examples

Connect a user’s BigQuery account and make API calls on their behalf — Scalekit handles OAuth and token management automatically.

Proxy API Calls

Node.js

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

const connectionName = 'bigquery'; // 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;

// Authenticate the user
const { link } = await actions.getAuthorizationLink({
  connectionName,
  identifier,
});
console.log('🔗 Authorize BigQuery:', link);
process.stdout.write('Press Enter after authorizing...');
await new Promise(r => process.stdin.once('data', r));

// Make a request via Scalekit proxy
const result = await actions.request({
  connectionName,
  identifier,
  path: '/bigquery/v2/projects',
  method: 'GET',
});
console.log(result);

Python

import scalekit.client, os
from dotenv import load_dotenv
load_dotenv()

connection_name = "bigquery"  # get your connection name from connection configurations
identifier = "user_123"     # your unique user identifier

# Get your credentials from app.scalekit.com → Developers → Settings → API Credentials
scalekit_client = scalekit.client.ScalekitClient(
    client_id=os.getenv("SCALEKIT_CLIENT_ID"),
    client_secret=os.getenv("SCALEKIT_CLIENT_SECRET"),
    env_url=os.getenv("SCALEKIT_ENV_URL"),
)
actions = scalekit_client.actions

# Authenticate the user
link_response = actions.get_authorization_link(
    connection_name=connection_name,
    identifier=identifier
)
# present this link to your user for authorization, or click it yourself for testing
print("🔗 Authorize BigQuery:", link_response.link)
input("Press Enter after authorizing...")

# Make a request via Scalekit proxy
result = actions.request(
    connection_name=connection_name,
    identifier=identifier,
    path="/bigquery/v2/projects",
    method="GET"
)
print(result)