Data Agents tools for ADK

Supported in ADKPython v1.23.0

These are a set of tools aimed to provide integration with Data Agents powered by Conversational Analytics API.

Data Agents are AI-powered agents that help you analyze your data using natural language. When configuring a Data Agent, you can choose from supported data sources, including BigQuery, Looker, and Looker Studio.

Prerequisites

Before using these tools, you must build and configure your Data Agents in Google Cloud:

• Build a data agent using HTTP and Python
• Build a data agent using the Python SDK
• Create a data agent in BigQuery Studio

The DataAgentToolset includes the following tools:

• list_accessible_data_agents: Lists Data Agents you have permission to access in the configured GCP project.
• get_data_agent_info: Retrieves details about a specific Data Agent given its full resource name.
• ask_data_agent: Chats with a specific Data Agent using natural language.

They are packaged in the toolset DataAgentToolset.

# Copyright 2026 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

import asyncio

from google.adk.agents import Agent
from google.adk.runners import Runner
from google.adk.sessions import InMemorySessionService
from google.adk.tools.data_agent.config import DataAgentToolConfig
from google.adk.tools.data_agent.credentials import DataAgentCredentialsConfig
from google.adk.tools.data_agent.data_agent_toolset import DataAgentToolset
from google.genai import types
import google.auth

# Define constants for this example agent
AGENT_NAME = "data_agent_example"
APP_NAME = "data_agent_app"
USER_ID = "user1234"
SESSION_ID = "1234"
GEMINI_MODEL = "gemini-2.5-flash"

# Define tool configuration
tool_config = DataAgentToolConfig(
    max_query_result_rows=100,
)

# Use Application Default Credentials (ADC)
# https://cloud.google.com/docs/authentication/provide-credentials-adc
application_default_credentials, _ = google.auth.default()
credentials_config = DataAgentCredentialsConfig(
    credentials=application_default_credentials
)

# Instantiate a Data Agent toolset
da_toolset = DataAgentToolset(
    credentials_config=credentials_config,
    data_agent_tool_config=tool_config,
    tool_filter=[
        "list_accessible_data_agents",
        "get_data_agent_info",
        "ask_data_agent",
    ],
)

# Agent Definition
data_agent = Agent(
    name=AGENT_NAME,
    model=GEMINI_MODEL,
    description="Agent to answer user questions using Data Agents.",
    instruction=(
        "## Persona\nYou are a helpful assistant that uses Data Agents"
        " to answer user questions about their data.\n\n"
    ),
    tools=[da_toolset],
)

# Session and Runner
session_service = InMemorySessionService()
session = asyncio.run(
    session_service.create_session(
        app_name=APP_NAME, user_id=USER_ID, session_id=SESSION_ID
    )
)
runner = Runner(
    agent=data_agent, app_name=APP_NAME, session_service=session_service
)


# Agent Interaction
def call_agent(query):
    """
    Helper function to call the agent with a query.
    """
    content = types.Content(role="user", parts=[types.Part(text=query)])
    events = runner.run(user_id=USER_ID, session_id=SESSION_ID, new_message=content)

    print("USER:", query)
    for event in events:
        if event.is_final_response():
            final_response = event.content.parts[0].text
            print("AGENT:", final_response)


call_agent("List accessible data agents in project <PROJECT_ID>.")
call_agent("Get information about <DATA_AGENT_NAME>.")
# The data agent in this example is configured with the BigQuery table:
# `bigquery-public-data.san_francisco.street_trees`
call_agent("Ask <DATA_AGENT_NAME> to count the rows in the table.")
call_agent("What are the columns in the table?")
call_agent("What are the top 5 tree species?")
call_agent("For those species, what is the distribution of legal status?")