BigQuery (Service Account) connector for AI agents

BigQuery (Service Account) tools for AI agents

CALL ANY TOOL

12 tools covering get, dry, cancel.

bigqueryserviceaccount_cancel_job

Request cancellation of a running bigquery job. returns the

Request cancellation of a running bigquery job. returns the final job resource. cancellation is best-effort and the job may complete before it can be cancelled.

Parameters

Name

Type

Required

Description

job_id

string

Required

The ID of the job to cancel

location

string

Optional

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

bigqueryserviceaccount_dry_run_query

Validate a sql query and estimate its cost without executing

bigqueryserviceaccount_get_dataset

Retrieve metadata for a specific bigquery dataset, including

bigqueryserviceaccount_get_job

Retrieve the status and configuration of a bigquery job by i

bigqueryserviceaccount_get_model

Retrieve metadata for a specific bigquery ml model, includin

bigqueryserviceaccount_get_query_results

Retrieve the results of a completed bigquery query job. supp

bigqueryserviceaccount_get_routine

Retrieve the definition and metadata of a specific bigquery

bigqueryserviceaccount_get_table

Retrieve metadata and schema for a specific bigquery table o

bigqueryserviceaccount_insert_query_job

Submit an asynchronous bigquery query job. returns a job id

bigqueryserviceaccount_list_datasets

List all bigquery datasets in the project. supports filterin

bigqueryserviceaccount_list_jobs

List bigquery jobs in the project. supports filtering by sta

bigqueryserviceaccount_list_models

List all bigquery ml models in a dataset, including their mo

Build your Agent

Same auth pattern across every framework.

from langchain_mcp_adapters.client import MultiServerMCPClient
from scalekit import ScalekitClient

client = ScalekitClient(env_url=ENV_URL, client_id=CLIENT_ID, client_secret=SECRET)
token = client.agent.get_token(user_id="user_id", connector="bigqueryserviceaccount")

mcp = MultiServerMCPClient({
    "bigqueryserviceaccount": {
        "url": "https://mcp.scalekit.com/bigqueryserviceaccount",
        "headers": {"Authorization": "Bearer " + token}
    }
})
tools = await mcp.get_tools()

import OpenAI from "openai";
import { ScalekitClient } from "@scalekit-sdk/node";

const client = new ScalekitClient({ envUrl, clientId, clientSecret });
const token = await client.agent.getToken({ userId: "user_id", connector: "bigqueryserviceaccount" });

const openai = new OpenAI();
// Connect to MCP at https://mcp.scalekit.com/bigqueryserviceaccount
// Pass: Authorization: Bearer + token

import Anthropic from "@anthropic-ai/sdk";
import { ScalekitClient } from "@scalekit-sdk/node";

const client = new ScalekitClient({ envUrl, clientId, clientSecret });
const token = await client.agent.getToken({ userId: "user_id", connector: "bigqueryserviceaccount" });

const anthropic = new Anthropic();
// Connect to MCP at https://mcp.scalekit.com/bigqueryserviceaccount
// Pass: Authorization: Bearer + token

from google.adk.agents import LlmAgent
from scalekit import ScalekitClient

client = ScalekitClient(env_url=ENV_URL, client_id=CLIENT_ID, client_secret=SECRET)
token = client.agent.get_token(user_id="user_id", connector="bigqueryserviceaccount")
# Connect to MCP at https://mcp.scalekit.com/bigqueryserviceaccount
# Pass: Authorization: Bearer + token

Try these prompts

Paste any prompt into your agent to get started.

Get started

Copy the prompt

Copied

Submit an asynchronous BigQuery query job?

Copy the prompt

Copied

Request cancellation of a running BigQuery job?

Advanced

Copy the prompt

Copied

Validate a SQL query and estimate its cost without executing it?

Copy the prompt

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List all tables and views in a BigQuery dataset?

SEE HOW AUTH WORKS

User authorises once. Every agent call after uses their token with scope enforcement.

Authorize

Your user connects

BigQuery (Service Account)

once. We tie it to their identity and the meetings they approved — no shared bot account, no org-wide access

Who:

user ‘A’

when:

Once per user

access:

Limited to user

Store

Their

BigQuery (Service Account)

token lives in a vault scoped to them. User A's meetings are never reachable by an agent acting for user B, even on the same connection

vault:

encrypted

scope:

per-user

tokens:

auto-refreshed

Resolve

When your agent calls a

BigQuery (Service Account)

tool, we fetch the right token server-side. It never touches your agent, never appears in the LLM context, never shows up in your logs

speed:

~40ms

check:

before every call

seen by:

nobody

Audit

Every

BigQuery (Service Account)

tool call is logged — who triggered it, which meeting was fetched, what came back. 90 days of history, tied to the user who authorized it

history:

90 days

export:

SIEM-ready

logged:

every call

Test other agents

See the same per-user auth pattern across other connectors.

SALES

Deal intelligence agent

Combine Gong, Attio, and Slack signals to surface deal risks and next-best actions. Updated after every call.

ENGINEERING

Engineering standup agent

Aggregate GitHub and GitLab activity, link to Jira, and post a daily standup digest to Slack. No async updates.

Why Scalekit

Secure your agent's access. Connectors ship in minutes

Other connector libraries treat auth as a demo afterthought.

01.

Shared tokens break per-user analytics

A shared token looks fine in a demo. In production every call looks like a service account. Scalekit resolves the real user credential.

// shared token
 audit → bot_service_account

 // scalekit
 audit → user_abc ✓

02.

Authentication is not authorization

03.

Multi-tenancy is architectural

04.

One connector today. Ten tomorrow.

“Our agents act across Salesforce, Gong, Google Drive, and more, on behalf of every customer. Scalekit behind the scenes meant we can keep adding tools without ever rebuilding how credentials or tool calling work.”

Venu Madhav Kattagoni

Head of Engineering / Von

FAQs

Frequently Asked Questions

Does the agent access BigQuery (Service Account) as the user or as a shared key?
As the user. Each workspace member authorizes once and Scalekit resolves their credential at request time. Audit logs attribute every action to that user, not a shared service account.

Where is the BigQuery (Service Account) service account key stored?
In Scalekit's managed AES-256 token vault, namespaced per tenant. Refresh is automatic. Revocation is a single dashboard action. Tokens never appear in prompts, logs, or LLM context.

Can I limit what the agent is allowed to do in BigQuery (Service Account)?
Yes. Pass a tool name filter to listScopedTools so the analytics agent only sees the subset you authorize. Pre-API-call scope checks block out-of-policy actions before the request reaches BigQuery (Service Account).

What happens when a user revokes BigQuery (Service Account) access?
The connection is invalidated on the next tool call. Subsequent requests for that user fail closed with a clear error. Other users in the tenant remain unaffected. The event is logged for audit.

Does the service account respect BigQuery IAM?
Yes. Queries run under the connected service account's IAM roles, with dataset ACLs, row-level security, and masking intact. Scalekit vaults the key and adds per-call scope checks plus audit.

On this page

Tool and actions Framework Compatibility Starter Prompt Auth Lifecycle Try Other Agents Why Scalekit