Google BigQuery connector

1. Install the SDK

   Node.js

   npm install @scalekit-sdk/node

   Python

   pip install scalekit

   Full SDK reference: Node.js | Python

2. Set your credentials

   Add your Scalekit credentials to your .env file. Find values in app.scalekit.com > Developers > API Credentials.

   .env

   SCALEKIT_ENVIRONMENT_URL=<your-environment-url>
   SCALEKIT_CLIENT_ID=<your-client-id>
   SCALEKIT_CLIENT_SECRET=<your-client-secret>

3. Set up the connector

   Register your Google BigQuery credentials with Scalekit so it handles the token lifecycle. You do this once per environment.

   Dashboard setup steps

   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 AgentKit > Connections > 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 AgentKit > 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.

4. Authorize and make your first call

   Node.js

   quickstart.ts

   import { ScalekitClient } from '@scalekit-sdk/node'
   import 'dotenv/config'
   
   const scalekit = new ScalekitClient(
     process.env.SCALEKIT_ENV_URL,
     process.env.SCALEKIT_CLIENT_ID,
     process.env.SCALEKIT_CLIENT_SECRET,
   )
   const actions = scalekit.actions
   
   const connector = 'bigquery'
   const identifier = 'user_123'
   
   // Generate an authorization link for the user
   const { link } = await actions.getAuthorizationLink({ connectionName: connector, identifier })
   console.log('Authorize Google BigQuery:', link)
   process.stdout.write('Press Enter after authorizing...')
   await new Promise(r => process.stdin.once('data', r))
   
   // Make your first API call through the proxy
   const result = await actions.request({
     connectionName: connector,
     identifier,
     path: '/bigquery/v2/projects',
     method: 'GET',
   })
   console.log(result)

   Python

   quickstart.py

   import os
   from scalekit.client import ScalekitClient
   from dotenv import load_dotenv
   load_dotenv()
   
   scalekit_client = ScalekitClient(
       env_url=os.getenv("SCALEKIT_ENV_URL"),
       client_id=os.getenv("SCALEKIT_CLIENT_ID"),
       client_secret=os.getenv("SCALEKIT_CLIENT_SECRET"),
   )
   actions = scalekit_client.actions
   
   connection_name = "bigquery"
   identifier = "user_123"
   
   # Generate an authorization link for the user
   link_response = actions.get_authorization_link(
       connection_name=connection_name,
       identifier=identifier,
   )
   print("Authorize Google BigQuery:", link_response.link)
   input("Press Enter after authorizing...")
   
   # Make your first API call through the proxy
   result = actions.request(
       connection_name=connection_name,
       identifier=identifier,
       path="/bigquery/v2/projects",
       method="GET",
   )
   print(result)

Common workflows

Proxy API call

Node.js

const result = await actions.request({
  connectionName: 'bigquery',
  identifier: 'user_123',
  path: '/bigquery/v2/projects',
  method: 'GET',
});
console.log(result);

Python

result = actions.request(
    connection_name='bigquery',
    identifier='user_123',
    path="/bigquery/v2/projects",
    method="GET",
)
print(result)

Execute a tool

Node.js

const result = await actions.executeTool({
  connector: 'bigquery',
  identifier: 'user_123',
  toolName: 'bigquery_list',
  toolInput: {},
});
console.log(result);

Python

result = actions.execute_tool(
    connection_name='bigquery',
    identifier='user_123',
    tool_name='bigquery_list',
    tool_input={},
)
print(result)