Google BigQuery MCP server for AI agents and assistants

Securely connect your AI agents and chatbots (Claude, ChatGPT, Cursor, etc) with Google BigQuery MCP or direct API to run complex SQL queries, analyze datasets, update tables, and automate reporting through natural language.

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Google BigQuery is a fully managed cloud data warehouse for fast SQL analytics on massive datasets. It's designed to help you analyze big data with ease, speed, and built-in machine learning.

63 Tools

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TOOL ROUTER PLAYGROUND
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TOOLS

Supported Tools

Every Google BigQuery action and event your agent gets out of the box.

Cancel BigQuery Job

Tool to cancel a running BigQuery job.

Create Capacity Commitment

Tool to create a new capacity commitment resource in BigQuery Reservation.

Create BigQuery Connection

Tool to create a new BigQuery connection to external data sources using the BigQuery Connection API.

Create Analytics Hub Data Exchange

Tool to create a new Analytics Hub data exchange for sharing BigQuery datasets.

Create Analytics Hub Listing

Tool to create a new listing in a BigQuery Analytics Hub data exchange.

Create BigQuery Dataset

Tool to create a new BigQuery dataset with explicit location, labels, and description using the BigQuery Datasets API.

Create Analytics Hub Listing

Tool to create a new listing in a data exchange using Analytics Hub API.

Create BigQuery Data Policy (v2beta1)

Tool to create a new data policy under a project with specified location using the v2beta1 BigQuery Data Policy API.

Create Analytics Hub Query Template

Tool to create a new query template in a BigQuery Analytics Hub Data Clean Room (DCR) data exchange.

Create BigQuery Reservation

Tool to create a new BigQuery reservation resource to guarantee compute capacity (slots) for query and pipeline jobs.

Create BigQuery Reservation Assignment

Tool to create a BigQuery reservation assignment that allows a project, folder, or organization to submit jobs using slots from a specified reservation.

Create BigQuery Routine

Tool to create a new user-defined routine (function or procedure) in a BigQuery dataset.

Create BigQuery Table

Tool to create a new, empty table in a BigQuery dataset.

Delete BigQuery Dataset

Tool to delete a BigQuery dataset specified by datasetId via the datasets.

Delete BigQuery Job Metadata

Tool to delete the metadata of a BigQuery job.

Delete BigQuery ML Model

Tool to delete a BigQuery ML model from a dataset.

Delete BigQuery Routine

Tool to delete a BigQuery routine by its ID.

Delete BigQuery Table

Tool to delete a BigQuery table from a dataset.

Get BigQuery ML Model

Tool to retrieve a specific BigQuery ML model resource by model ID.

Get BigQuery Connection IAM Policy

Tool to get the IAM access control policy for a BigQuery connection resource.

Get BigQuery Dataset Metadata

Tool to retrieve BigQuery dataset metadata including location via the datasets.

Get BigQuery Job

Tool to retrieve information about a specific BigQuery job.

Get BigQuery Query Results

Tool to get the results of a BigQuery query job via RPC.

Get BigQuery Routine

Tool to retrieve a BigQuery routine (user-defined function or stored procedure) by its ID.

Get BigQuery Routine IAM Policy

Tool to retrieve the IAM access control policy for a BigQuery routine resource.

Get BigQuery Service Account

Tool to get the service account for a project used for interactions with Google Cloud KMS.

Get BigQuery Table IAM Policy

Tool to retrieve the IAM access control policy for a BigQuery table resource.

Get BigQuery Table Schema

Tool to fetch a BigQuery table's schema and metadata without querying row data.

Insert Data into BigQuery Table

Tool to stream data into BigQuery one record at a time without running a load job.

Insert BigQuery Job

Tool to start a new asynchronous BigQuery job (query, load, extract, or copy).

Insert BigQuery Job with Upload

Tool to start a new BigQuery load job with file upload.

List Analytics Hub Listings

Tool to list all listings in a given Analytics Hub data exchange.

List BigQuery Connections

Tool to list BigQuery connections in a given project and location.

List BigQuery Capacity Commitments

Tool to list all capacity commitments for the admin project.

List Data Exchange Listings

Tool to list all listings in a given Analytics Hub data exchange using the v1beta1 API.

List BigQuery Datasets

Tool to list datasets in a specific BigQuery project, including dataset locations.

List BigQuery Jobs

Tool to list all jobs that you started in a BigQuery project.

List BigQuery Data Transfer Locations

Tool to list information about supported locations for BigQuery Data Transfer Service.

List Connections in Location

Tool to list BigQuery connections in a given project and location using the v1beta1 API.

List BigQuery Location Data Policies

Tool to list all data policies in a specified parent project and location using the v2beta1 API.

List BigQuery Models

Tool to list all BigQuery ML models in a specified dataset.

List Organization Data Exchanges

Tool to list all data exchanges from projects in a given organization and location using Analytics Hub API.

List BigQuery Projects

Tool to list BigQuery projects to which the user has been granted any project role.

List Analytics Hub Query Templates

Tool to list all query templates in a given Analytics Hub data exchange.

List BigQuery Reservation Assignments

Tool to list BigQuery reservation assignments.

List BigQuery Reservation Groups

Tool to list all BigQuery reservation groups for a project in a specified location.

List BigQuery Reservations

Tool to list all BigQuery reservations for a project in a specified location.

List BigQuery Routines

Tool to list all routines (user-defined functions and stored procedures) in a BigQuery dataset.

List BigQuery Row Access Policies

Tool to list all row access policies on a specified BigQuery table.

List BigQuery Table Data

Tool to list the content of a BigQuery table in rows via the REST API.

List BigQuery Tables

Tool to list tables in a BigQuery dataset via the REST API.

Patch BigQuery Dataset

Tool to update an existing BigQuery dataset using RFC5789 PATCH semantics.

Patch BigQuery ML Model

Tool to update specific fields in an existing BigQuery ML model using PATCH semantics.

Patch BigQuery Table

Tool to update specific fields in an existing BigQuery table using RFC5789 PATCH semantics.

Query

Query Tool runs a SQL query in BigQuery using the REST API.

Search All BigQuery Reservation Assignments

Tool to search all BigQuery reservation assignments for a specified resource in a particular region.

Set BigQuery Routine IAM Policy

Tool to set the IAM access control policy for a BigQuery routine resource.

Test BigQuery Routine IAM Permissions

Tool to test which IAM permissions the caller has on a BigQuery routine.

Undelete BigQuery Dataset

Tool to undelete a BigQuery dataset within the time travel window.

Update BigQuery Connection

Tool to update a specified BigQuery connection using the BigQuery Connection API.

Update BigQuery Dataset

Tool to update information in an existing BigQuery dataset using the PUT method.

Update BigQuery Routine

Tool to update an existing BigQuery routine (function or stored procedure).

Update BigQuery Table

Tool to update an existing BigQuery table.

SETUP GUIDE

Connect Google BigQuery MCP Tool with your Agent

1

Install Composio

typescript
npm install @composio/core ai @ai-sdk/mcp @ai-sdk/openai
Install the Composio SDK and your agent framework
2

Create a session with MCP enabled

typescript
import { Composio } from "@composio/core";

const composio = new Composio();
const { mcp } = await composio.create("your-user-id", {
  toolkits: ["googlebigquery"],
  mcp: true,
});
Create a session scoped to Google BigQuery and read its MCP URL and headers
3

Connect your agent to the MCP server

typescript
import { createMCPClient } from "@ai-sdk/mcp";
import { openai } from "@ai-sdk/openai";
import { generateText, stepCountIs } from "ai";

const client = await createMCPClient({
  transport: { type: "http", url: mcp.url, headers: mcp.headers },
});

const { text } = await generateText({
  model: openai("gpt-5.6-sol"),
  tools: await client.tools(),
  prompt: "Show total sales by region for last month",
  stopWhen: stepCountIs(10),
});

console.log(text);
await client.close();
Pass the session's MCP URL and headers to your agent and run a Google BigQuery request
SETUP GUIDE

Connect Google BigQuery API Tool with your Agent

1

Install Composio

typescript
npm install @composio/core @composio/openai openai
Install the Composio SDK, the OpenAI provider, and the OpenAI SDK
2

Create a Composio session

typescript
import OpenAI from "openai";
import { Composio } from "@composio/core";
import { OpenAIResponsesProvider } from "@composio/openai";

const composio = new Composio({ provider: new OpenAIResponsesProvider() });
const client = new OpenAI();

const session = await composio.create("your-user-id", { toolkits: ["googlebigquery"] });
const tools = await session.tools();
Initialize Composio with the OpenAI Responses provider and create a session scoped to Google BigQuery
3

Run Google BigQuery tools with your agent

typescript
let response = await client.responses.create({
  model: "gpt-5.6-sol",
  tools,
  input: [{ role: "user", content: "Show total sales by region for last month" }],
});

while (response.output.some((o) => o.type === "function_call")) {
  const outputs = await composio.provider.handleToolCalls(session, response.output);
  response = await client.responses.create({
    model: "gpt-5.6-sol",
    tools,
    previous_response_id: response.id,
    input: outputs,
  });
}

console.log(response.output_text);
Send a request, execute the Google BigQuery tool calls through the session, and print the final answer

Why Use Composio?

AI Native Google BigQuery Integration

  • Supports both Google BigQuery MCP and direct API based integrations
  • Structured, LLM-friendly schemas for reliable tool execution
  • Rich coverage for reading, writing, and querying your Google BigQuery data

Managed Auth

  • Built-in OAuth handling with automatic token refresh and rotation
  • Central place to manage, scope, and revoke Google BigQuery access
  • Per user and per environment credentials instead of hard-coded keys

Agent Optimized Design

  • Tools are tuned using real error and success rates to improve reliability over time
  • Comprehensive execution logs so you always know what ran, when, and on whose behalf

Enterprise Grade Security

  • Fine-grained RBAC so you control which agents and users can access Google BigQuery
  • Scoped, least privilege access to Google BigQuery resources
  • Full audit trail of agent actions to support review and compliance

Rolling this out across your team?

Give your team centralized access control across every framework with Composio’s MCP Gateway.

EXPLORE MCP GATEWAY
FAQ

Frequently asked questions

Google BigQuery requires connections to go through your own OAuth app. You register it once with Google BigQuery, add its client ID and secret in the Composio dashboard, and from then on everyone connects by signing in to Google BigQuery as usual. Composio handles the rest of the flow and the token refresh.

Yes! Composio's Tool Router enables agents to use multiple toolkits. Learn more.

Yes. Composio is SOC 2 Type II compliant and is built to keep your Google BigQuery connection and credentials secure. OAuth tokens and API keys are encrypted, and sensitive customer data is protected at rest and in transit.

Composio also undergoes independent security testing and continuously monitors its systems for security threats. You can review the latest reports and policies in the Composio Trust Center.

Composio maintains and updates all toolkit integrations automatically, so your agents always work with the latest API versions.

When you connect a Google BigQuery account through Composio, every action runs under that account, so anything the agent creates, sends, or changes shows up in Google BigQuery as done by you. Keep an approval step in your prompt for actions with side effects, such as sending or deleting, and have the agent draft first.

Exactly the ones Google BigQuery lists on its consent screen when you connect. Review that screen before approving. If you connect a work account, your Google BigQuery administrator may need to approve the app first, and you can revoke the access inside Google BigQuery whenever you want.

Yes. Composio supports multiple connected accounts for the same app, and that works in Claude, ChatGPT, or any other assistant you connect through Composio. Give each Google BigQuery connection a name such as work or personal, and the assistant uses the one you mention in the request. Each account keeps its own credentials and nothing is merged.

Composio refreshes Google BigQuery tokens automatically, so day to day you do nothing. If you revoke access inside Google BigQuery, or Google BigQuery invalidates the session, the connection shows as expired in Composio and the agent stops acting on that account until you reconnect it, which is a single sign-in.

Composio's free Hobby plan includes 100,000 tool calls per month with no credit card, which covers most personal Google BigQuery use. Paid plans add higher limits and team features. Your Google BigQuery plan and its API limits still apply as usual.

Built-in connectors usually give one AI access to a limited set of apps. Many people use Composio because it lets their AI connect to more apps than it normally supports, or connect to multiple accounts for the same app (e.g. connect Claude to multiple Google BigQuery accounts).

With Composio, you connect Google BigQuery once and then use it across different AI assistants without setting it up separately in each one. Connect your apps to Composio once, then connect Composio to whichever AI you use, whether that's Claude, ChatGPT, Hermes, or your own custom assistant.

Start with Google BigQuery.It takes 30 seconds.

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