How to integrate Google BigQuery MCP with Google ADK

BOOK A CALLGET STARTED FOR FREE
Framework Integration Gradient
Google BigQuery Logo
Google ADK Logo
divider

Introduction

This guide walks you through connecting Google BigQuery to Google ADK using the Composio tool router. By the end, you'll have a working Google BigQuery agent that can run yesterday's sales summary query, find top 10 customers by revenue, analyze traffic data for last quarter, get failed transactions count this week through natural language commands.

This guide will help you understand how to give your Google ADK agent real control over a Google BigQuery account through Composio's Google BigQuery MCP server.

Before we dive in, let's take a quick look at the key ideas and tools involved.

TL;DR

Here's what you'll learn:
  • Get a Google BigQuery account set up and connected to Composio
  • Install the Google ADK and Composio packages
  • Create a Composio Tool Router session for Google BigQuery
  • Build an agent that connects to Google BigQuery through MCP
  • Interact with Google BigQuery using natural language

What is Google ADK?

Google ADK (Agents Development Kit) is Google's framework for building AI agents powered by Gemini models. It provides tools for creating agents that can use external services through the Model Context Protocol.

Key features include:

  • Gemini Integration: Native support for Google's Gemini models
  • MCP Toolset: Built-in support for Model Context Protocol tools
  • Streamable HTTP: Connect to external services through streamable HTTP
  • CLI and Web UI: Run agents via command line or web interface

What is the Google BigQuery MCP server, and what's possible with it?

The Google BigQuery MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Google BigQuery account. It provides structured and secure access to your data warehouse, so your agent can perform actions like running SQL queries, analyzing datasets, extracting insights, and automating reporting on your behalf.

  • Instant SQL query execution: Have your agent run complex analytical queries on any of your BigQuery datasets and get results in real time.
  • Custom data analysis and reporting: Instruct your agent to generate summaries, trends, or statistics by querying specific tables or views.
  • Automated data extraction: Let your agent fetch and transform data for integration with other tools or for further analysis.
  • Interactive business intelligence: Enable your agent to answer ad hoc data questions, visualize aggregated data, or pull specific metrics from massive datasets instantly.
  • Streamlined workflow automation: Use your agent to automate recurring BigQuery tasks, such as daily audits or data slice generation, without manual effort.

Supported Tools & Triggers

Tools
QueryQuery tool will run a sql query in bigquery.

What is the Composio tool router, and how does it fit here?

What is Tool Router?

Composio's Tool Router helps agents find the right tools for a task at runtime. You can plug in multiple toolkits (like Gmail, HubSpot, and GitHub), and the agent will identify the relevant app and action to complete multi-step workflows. This can reduce token usage and improve the reliability of tool calls. Read more here: Getting started with Tool Router

The tool router generates a secure MCP URL that your agents can access to perform actions.

How the Tool Router works

The Tool Router follows a three-phase workflow:

  1. Discovery: Searches for tools matching your task and returns relevant toolkits with their details.
  2. Authentication: Checks for active connections. If missing, creates an auth config and returns a connection URL via Auth Link.
  3. Execution: Executes the action using the authenticated connection.

Step-by-step Guide

Prerequisites

Before starting, make sure you have:
  • A Google API key for Gemini models
  • A Composio account and API key
  • Python 3.9 or later installed
  • Basic familiarity with Python

Getting API Keys for Google and Composio

Google API Key
  • Go to Google AI Studio and create an API key.
  • Copy the key and keep it safe. You will put this in GOOGLE_API_KEY.
Composio API Key and User ID
  • Log in to the Composio dashboard.
  • Go to Settings → API Keys and copy your Composio API key. Use this for COMPOSIO_API_KEY.
  • Decide on a stable user identifier to scope sessions, often your email or a user ID. Use this for COMPOSIO_USER_ID.

Install dependencies

bash
pip install google-adk composio-google python-dotenv

Inside your virtual environment, install the required packages.

What's happening:

  • google-adk is Google's Agents Development Kit
  • composio connects your agent to Google BigQuery via MCP
  • composio-google provides the Google ADK provider
  • python-dotenv loads environment variables

Set up ADK project

bash
adk create my_agent

Set up a new Google ADK project.

What's happening:

  • This creates an agent folder with a root agent file and .env file

Set environment variables

bash
GOOGLE_API_KEY=your-google-api-key
COMPOSIO_API_KEY=your-composio-api-key
COMPOSIO_USER_ID=your-user-id-or-email

Save all your credentials in the .env file.

What's happening:

  • GOOGLE_API_KEY authenticates with Google's Gemini models
  • COMPOSIO_API_KEY authenticates with Composio
  • COMPOSIO_USER_ID identifies the user for session management

Import modules and validate environment

python
import os
import warnings

from composio import Composio
from composio_google import GoogleProvider
from dotenv import load_dotenv
from google.adk.agents.llm_agent import Agent
from google.adk.tools.mcp_tool.mcp_session_manager import StreamableHTTPConnectionParams
from google.adk.tools.mcp_tool.mcp_toolset import McpToolset

load_dotenv()

warnings.filterwarnings("ignore", message=".*BaseAuthenticatedTool.*")

GOOGLE_API_KEY = os.getenv("GOOGLE_API_KEY")
COMPOSIO_API_KEY = os.getenv("COMPOSIO_API_KEY")
COMPOSIO_USER_ID = os.getenv("COMPOSIO_USER_ID")

if not GOOGLE_API_KEY:
    raise ValueError("GOOGLE_API_KEY is not set in the environment.")
if not COMPOSIO_API_KEY:
    raise ValueError("COMPOSIO_API_KEY is not set in the environment.")
if not COMPOSIO_USER_ID:
    raise ValueError("COMPOSIO_USER_ID is not set in the environment.")
What's happening:
  • os reads environment variables
  • Composio is the main Composio SDK client
  • GoogleProvider declares that you are using Google ADK as the agent runtime
  • Agent is the Google ADK LLM agent class
  • McpToolset lets the ADK agent call MCP tools over HTTP

Create Composio client and Tool Router session

python
print("Initializing Composio client...")
composio_client = Composio(api_key=COMPOSIO_API_KEY, provider=GoogleProvider())

print("Creating Composio session...")
composio_session = composio_client.create(
    user_id=COMPOSIO_USER_ID,
    toolkits=["googlebigquery"],
)

COMPOSIO_MCP_URL = composio_session.mcp.url
print(f"Composio MCP HTTP URL: {COMPOSIO_MCP_URL}")
What's happening:
  • Authenticates to Composio with your API key
  • Declares Google ADK as the provider
  • Spins up a short-lived MCP endpoint for your user and selected toolkit
  • Stores the MCP HTTP URL for the ADK MCP integration

Set up the McpToolset and create the Agent

python
print("Creating Composio toolset for the agent...")
composio_toolset = McpToolset(
    connection_params=StreamableHTTPConnectionParams(
        url=COMPOSIO_MCP_URL,
        headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")}
    )
)

root_agent = Agent(
    model="gemini-2.5-pro",
    name="composio_agent",
    description="An agent that uses Google BigQuery tools to perform actions.",
    instruction=(
        "You are a helpful assistant connected to Composio. "
        "You have the following tools available: "
        "COMPOSIO_SEARCH_TOOLS, COMPOSIO_MULTI_EXECUTE_TOOL, "
        "COMPOSIO_MANAGE_CONNECTIONS, COMPOSIO_REMOTE_BASH_TOOL, COMPOSIO_REMOTE_WORKBENCH. "
        "Use these tools to help users with Google BigQuery operations."
    ),
    tools=[composio_toolset],
)

print("\nAgent setup complete. You can now run this agent directly ;)")
What's happening:
  • Connects the ADK agent to the Composio MCP endpoint through McpToolset
  • Uses Gemini as the model powering the agent
  • Lists exact tool names in instruction to reduce misnamed tool calls

Run the agent

bash
# Run in CLI mode
adk run my_agent

# Or run in web UI mode
adk web
Execute the agent from the project root. The web command opens a web portal where you can chat with the agent. What's happening:
  • adk run runs the agent in CLI mode
  • adk web opens a web UI for interactive testing

Complete Code

Here's the complete code to get you started with Google BigQuery and Google ADK:

python
import os
import warnings

from composio import Composio
from composio_google import GoogleProvider
from dotenv import load_dotenv
from google.adk.agents.llm_agent import Agent
from google.adk.tools.mcp_tool.mcp_session_manager import StreamableHTTPConnectionParams
from google.adk.tools.mcp_tool.mcp_toolset import McpToolset

def main():
    try:
        load_dotenv()

        warnings.filterwarnings("ignore", message=".*BaseAuthenticatedTool.*")

        GOOGLE_API_KEY = os.getenv("GOOGLE_API_KEY")
        COMPOSIO_API_KEY = os.getenv("COMPOSIO_API_KEY")
        COMPOSIO_USER_ID = os.getenv("COMPOSIO_USER_ID")

        if not GOOGLE_API_KEY:
            raise ValueError("GOOGLE_API_KEY is not set in the environment.")
        if not COMPOSIO_API_KEY:
            raise ValueError("COMPOSIO_API_KEY is not set in the environment.")
        if not COMPOSIO_USER_ID:
            raise ValueError("COMPOSIO_USER_ID is not set in the environment.")

        print("Initializing Composio client...")
        composio_client = Composio(api_key=COMPOSIO_API_KEY, provider=GoogleProvider())

        print("Creating Composio session...")
        composio_session = composio_client.create(
            user_id=COMPOSIO_USER_ID,
            toolkits=["googlebigquery"],
        )

        COMPOSIO_MCP_URL = composio_session.mcp.url
        print(f"Composio MCP HTTP URL: {COMPOSIO_MCP_URL}")

        print("Creating Composio toolset for the agent...")
        composio_toolset = McpToolset(
            connection_params=StreamableHTTPConnectionParams(
                url=COMPOSIO_MCP_URL,
                headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")}
            )
        )

        root_agent = Agent(
            model="gemini-2.5-pro",
            name="composio_agent",
            description="An agent that uses Google BigQuery tools to perform actions.",
            instruction=(
                "You are a helpful assistant connected to Composio. "
                "You have the following tools available: "
                "COMPOSIO_SEARCH_TOOLS, COMPOSIO_MULTI_EXECUTE_TOOL, "
                "COMPOSIO_MANAGE_CONNECTIONS, COMPOSIO_REMOTE_BASH_TOOL, COMPOSIO_REMOTE_WORKBENCH. "
                "Use these tools to help users with Google BigQuery operations."
            ),
            tools=[composio_toolset],
        )

        print("\nAgent setup complete. You can now run this agent directly ;)")

    except Exception as e:
        print(f"\nAn error occurred during agent setup: {e}")

if __name__ == "__main__":
    main()

Conclusion

You've successfully integrated Google BigQuery with the Google ADK through Composio's MCP Tool Router. Your agent can now interact with Google BigQuery using natural language commands.

Key takeaways:

  • The Tool Router approach dynamically routes requests to the appropriate Google BigQuery tools
  • Environment variables keep your credentials secure and separate from code
  • Clear agent instructions reduce tool calling errors
  • The ADK web UI provides an interactive interface for testing and development

You can extend this setup by adding more toolkits to the toolkits array in your session configuration.

How to build Google BigQuery MCP Agent with another framework

OpenAI Agents SDK

OpenAI Agents SDK

Use Google BigQuery MCP with OpenAI Agents SDK

Claude Agent SDK

Claude Agent SDK

Use Google BigQuery MCP with Claude Agent SDK

LangChain

LangChain

Use Google BigQuery MCP with LangChain

Vercel AI SDK

Vercel AI SDK

Use Google BigQuery MCP with Vercel AI SDK

Mastra AI

Mastra AI

Use Google BigQuery MCP with Mastra AI

LlamaIndex

LlamaIndex

Use Google BigQuery MCP with LlamaIndex

CrewAI

CrewAI

Use Google BigQuery MCP with CrewAI

FAQ

What are the differences in Tool Router MCP and Google BigQuery MCP?

With a standalone Google BigQuery MCP server, the agents and LLMs can only access a fixed set of Google BigQuery tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Google BigQuery and many other apps based on the task at hand, all through a single MCP endpoint.

Can I use Tool Router MCP with Google ADK?

Yes, you can. Google ADK fully supports MCP integration. You get structured tool calling, message history handling, and model orchestration while Tool Router takes care of discovering and serving the right Google BigQuery tools.

Can I manage the permissions and scopes for Google BigQuery while using Tool Router?

Yes, absolutely. You can configure which Google BigQuery scopes and actions are allowed when connecting your account to Composio. You can also bring your own OAuth credentials or API configuration so you keep full control over what the agent can do.

How safe is my data with Composio Tool Router?

All sensitive data such as tokens, keys, and configuration is fully encrypted at rest and in transit. Composio is SOC 2 Type 2 compliant and follows strict security practices so your Google BigQuery data and credentials are handled as safely as possible.

Used by agents from

Context
ASU
Letta
glean
HubSpot
Agent.ai
Altera
DataStax
Entelligence
Rolai
Context
ASU
Letta
glean
HubSpot
Agent.ai
Altera
DataStax
Entelligence
Rolai
Context
ASU
Letta
glean
HubSpot
Agent.ai
Altera
DataStax
Entelligence
Rolai

Never worry about agent reliability

We handle tool reliability, observability, and security so you never have to second-guess an agent action.

Book a call↗Get started for free