How to integrate Apify MCP with Google ADK

This guide walks you through connecting Apify to Google ADK using the Composio tool router. By the end, you'll have a working Apify agent that can create a new dataset for scraped results, fetch items from a specific apify dataset, get details of your latest apify actor through natural language commands. This guide will help you understand how to give your Google ADK agent real control over a Apify account through Composio's Apify MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

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Apify is a cloud platform for building, deploying, and managing web scraping and automation tools called Actors. It lets you automate data extraction and workflow tasks at scale—no infrastructure headaches.

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Introduction

This guide walks you through connecting Apify to Google ADK using the Composio tool router. By the end, you'll have a working Apify agent that can create a new dataset for scraped results, fetch items from a specific apify dataset, get details of your latest apify actor through natural language commands.

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

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

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TL;DR

Here's what you'll learn:
  • Get a Apify account set up and connected to Composio
  • Install the Google ADK and Composio packages
  • Create a Composio Tool Router session for Apify
  • Build an agent that connects to Apify through MCP
  • Interact with Apify 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 Apify MCP server, and what's possible with it?

The Apify MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Apify account. It provides structured and secure access to your web scraping and automation workflows, so your agent can create actors, manage datasets, fetch scraped data, schedule tasks, and maintain webhooks on your behalf.

  • Automated Actor Creation and Management: Easily instruct your agent to programmatically create, configure, or delete Apify actors for custom web automation or scraping jobs.
  • Dataset Handling and Data Retrieval: Let your agent spin up new datasets, organize scraped results, and pull items from datasets for downstream analysis or reporting.
  • Task Scheduling and Automation: Have your agent create and manage recurring actor tasks, making it simple to automate data extraction or browser automation at set intervals.
  • Webhook Integration and Event Handling: Direct your agent to set up or remove webhooks for actor tasks, enabling real-time notifications or downstream integrations when a task completes or fails.
  • Actor and Build Metadata Access: Empower your agent to fetch detailed metadata about actors, including build information and configuration details, for monitoring or troubleshooting purposes.

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

What is Composio SDK?

Composio's Composio SDK 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 Composio SDK

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

How the Composio SDK works

The Composio SDK 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

Step by step09 STEPS
1

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
2

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.
3

Install dependencies

bash
pip install google-adk composio 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 Apify via MCP
  • python-dotenv loads environment variables
4

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
5

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
6

Import modules and validate environment

python
import os
import warnings

from composio import Composio
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
7

Create Composio client and Tool Router session

python
composio_client = Composio(api_key=COMPOSIO_API_KEY)

composio_session = composio_client.create(
    user_id=COMPOSIO_USER_ID,
    toolkits=["apify"],
)

COMPOSIO_MCP_URL = composio_session.mcp.url,
print(f"Composio MCP 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
8

Set up the McpToolset and create the Agent

python
composio_toolset = McpToolset(
    connection_params=StreamableHTTPConnectionParams(
        url=COMPOSIO_MCP_URL,
        headers={"x-api-key": COMPOSIO_API_KEY}
    )
)

root_agent = Agent(
    model="gemini-2.5-flash",
    name="composio_agent",
    description="An agent that uses Composio 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 Apify 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
9

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 Apify 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

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.")

composio_client = Composio(api_key=COMPOSIO_API_KEY, provider=GoogleProvider())

composio_session = composio_client.create(
    user_id=COMPOSIO_USER_ID,
    toolkits=["apify"],
)

COMPOSIO_MCP_URL = composio_session.mcp.url


composio_toolset = McpToolset(
    connection_params=StreamableHTTPConnectionParams(
        url=COMPOSIO_MCP_URL,
        headers={"x-api-key": COMPOSIO_API_KEY}
    )
)

root_agent = Agent(
    model="gemini-2.5-flash",
    name="composio_agent",
    description="An agent that uses Composio 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 Apify operations."
    ),  
    tools=[composio_toolset],
)

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

Conclusion

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

Key takeaways:

  • The Tool Router approach dynamically routes requests to the appropriate Apify 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.

TOOLS

Supported Tools

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

Build Actor

Tool to build an Actor with specified configuration.

Abort Actor Build

Tool to abort an Actor build that is starting or running.

Delete Actor Build

Tool to delete an Actor build permanently.

Get Actor Build

Tool to get detailed information about a specific Actor build.

Get Actor Build Log

Tool to retrieve the log file for a specific Actor build.

Get user builds list

Tool to get a paginated list of all builds for a user.

Abort Actor Run

Tool to abort a running or starting Actor run.

Delete Actor Run

Tool to delete a finished Actor run.

Get Actor Run

Tool to get details about a specific Actor run.

Update Actor Run Status Message

Tool to update the status message of an Actor run.

Delete Actor Task

Tool to delete an Actor task permanently.

Get Actor Task

Tool to get complete details about an Actor task.

Update Actor Task

Tool to update Actor task settings using JSON payload.

Get last actor task run

Tool to get the most recent run of a specific Actor task.

Run Task Sync (GET)

Tool to run a specific task synchronously and return its output.

Run Task Sync & Get Dataset Items

Tool to run an actor task synchronously and retrieve its dataset items.

Run Task Sync with Input Override & Get Dataset Items

Tool to run an actor task synchronously with input overrides and retrieve its dataset items.

Run Task Sync (POST)

Tool to run an Actor task synchronously with input override and return its output.

Update Actor

Tool to update Actor settings using JSON payload.

Get last actor run

Tool to get the most recent run of a specific Actor.

Run Actor Sync without Input (GET)

Tool to run a specific Actor synchronously without input and return its output.

Run Actor Sync & Get Dataset Items

Tool to run Actor synchronously and get dataset items.

Get list of Actors

Tool to get the list of all Actors that the user created or used.

Delete Actor Version

Tool to delete a specific version of an Actor's source code.

Delete Actor Version Environment Variable

Tool to delete an environment variable from a specific Actor version.

Get Actor Version Environment Variable

Tool to get environment variable details for a specific Actor version.

Update Actor Version Environment Variable

Tool to update environment variable for a specific Actor version using JSON payload.

Get list of Actor version environment variables

Tool to get the list of environment variables for a specific Actor version.

Create Actor Version Environment Variable

Tool to create an environment variable for a specific Actor version.

Get Actor version

Tool to get details about a specific version of an Actor.

Update Actor Version

Tool to update an Actor version's configuration and source code.

Get list of Actor versions

Tool to get the list of versions of a specific Actor.

Create Actor Version

Tool to create a new version of an Actor.

Get list of Actor webhooks

Tool to get a list of webhooks for a specific Actor.

Create Actor

Tool to create a new Actor with specified configuration.

Create Dataset

Tool to create a new dataset.

Create Actor Task

Tool to create a new Actor task with specified settings.

Create Task Webhook

Tool to create a webhook for an Actor task.

Delete Dataset

Tool to delete a dataset permanently.

Get Dataset

Tool to retrieve dataset metadata by dataset ID.

Update Dataset

Tool to update a dataset's name via JSON payload.

Get list of datasets

Tool to get list of datasets for a user.

Get Dataset Statistics

Tool to get dataset field statistics by dataset ID.

Delete Actor

Tool to delete an Actor permanently.

Delete Webhook

Tool to delete a webhook by its ID.

Get Actor Details

Tool to get details of a specific Actor.

Get Actor Last Run Dataset Items

Tool to get dataset items from the last run of an Actor.

Get all webhooks

Tool to get a list of all webhooks created by the user.

Get dataset items

Tool to retrieve items from a dataset.

Get Default Build

Tool to get the default build for an Actor.

Get Key-Value Record

Tool to retrieve a record from a key-value store.

Get list of builds

Tool to get a list of builds for a specific Actor.

Get list of runs

Tool to get a list of runs for a specific Actor.

Get list of task runs

Tool to get a list of runs for a specific Actor task.

Get list of tasks

Tool to fetch a paginated list of tasks belonging to the authenticated user.

Get list of task webhooks

Tool to get a list of webhooks for a specific Actor task.

Get log

Tool to retrieve logs for a specific Actor run or build.

Get OpenAPI Definition

Tool to get the OpenAPI definition for a specific Actor build.

Get Run Dataset Items

Tool to get dataset items from a specific Actor run.

Get Task Input

Tool to retrieve the input configuration of a specific task.

Get Task Last Run Dataset Items

Tool to get dataset items from the last run of an Actor task.

Delete Key-Value Store

Tool to delete a key-value store permanently.

Get Key-Value Store

Tool to retrieve key-value store metadata by store ID.

Get Key-Value Store Keys

Tool to retrieve a list of keys from a key-value store.

Delete Key-Value Store Record

Tool to delete a record from a key-value store.

Check Key-Value Store Record Exists

Tool to check if a record exists in a key-value store.

Get list of key-value stores

Tool to get the list of key-value stores owned by the user.

Create Key-Value Store

Tool to create a new key-value store or retrieve an existing one by name.

List User Actor Runs

Tool to get a paginated list of all Actor runs for the authenticated user.

Delete Request Queue

Tool to delete a request queue permanently.

Get Request Queue

Tool to retrieve request queue metadata by queue ID.

Get Request Queue Head

Tool to retrieve first requests from the queue for inspection.

Get Head and Lock Queue Requests

Tool to get and lock head requests from the queue.

Update Request Queue

Tool to update request queue name using JSON payload.

Delete Request from Queue

Tool to delete a specific request from a request queue.

Get Request from Queue

Tool to retrieve a specific request from a request queue by its ID.

Delete Request Lock

Tool to delete a request lock from a request queue.

Prolong Request Lock

Tool to prolong request lock in a request queue.

Update Request in Queue

Tool to update a request in a request queue.

Batch Delete Requests from Queue

Tool to batch-delete up to 25 requests from a queue.

Batch Add Requests to Queue

Tool to batch-add up to 25 requests to a request queue.

List Request Queue Requests

Tool to list requests in a request queue with pagination support.

Add Request to Queue

Tool to add a request to the queue.

Unlock Queue Requests

Tool to unlock requests in a request queue that are currently locked by the client.

Get list of request queues

Tool to get list of request queues for a user.

Create Request Queue

Tool to create a new request queue or retrieve an existing one by name.

Run Actor Asynchronously

Tool to run a specific Actor asynchronously.

Run Actor Sync

Tool to run a specific Actor synchronously with input and return its output record.

Run Actor Sync & Get Dataset Items

Tool to run an Actor synchronously and retrieve its dataset items.

Run Task Asynchronously

Tool to run a specific Actor task asynchronously.

Delete Schedule

Tool to delete a schedule by its ID.

Get Schedule

Tool to get schedule details by ID.

Get Schedule Log

Tool to get schedule log by ID.

Update Schedule

Tool to update an existing schedule with new settings.

Get list of schedules

Tool to get list of schedules created by the user.

Create Schedule

Tool to create a new schedule with specified settings.

Store Data in Dataset

Tool to store data items in a dataset.

Store Data in Key-Value Store

Tool to create or update a record in a key-value store.

Get list of Actors in Store

Tool to get list of public Actors from Apify Store.

Update Key-Value Store

Tool to update a key-value store's properties.

Update Task Input

Tool to update the input configuration of a specific Actor task.

Get Public User Data

Tool to get public user data.

Get Current User Account Data

Tool to get private user account information.

Get Account Limits

Tool to get a complete summary of account limits and usage.

Update Account Limits

Tool to update account limits manageable on the Limits page.

Get Monthly Usage

Tool to get monthly usage summary with daily breakdown.

Get list of webhook dispatches

Tool to get list of webhook dispatches for the user.

Get Webhook Dispatch

Tool to get webhook dispatch object with all details.

Get webhook

Tool to get webhook object with all details.

Update Webhook

Tool to update webhook using JSON payload.

Test Webhook

Tool to test a webhook by creating a test dispatch with a dummy payload.

Get webhook dispatches

Tool to get list of webhook dispatches for a specific webhook.

FRAMEWORKS

How to build Apify MCP Agent with another framework

OpenAI Agents SDK logo

OpenAI Agents SDK

Use Apify MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use Apify MCP with Claude Agent SDK

Claude Code logo

Claude Code

Use Apify MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use Apify MCP with Claude Cowork

Codex logo

Codex

Use Apify MCP with Codex

OpenClaw logo

OpenClaw

Use Apify MCP with OpenClaw

Hermes logo

Hermes

Use Apify MCP with Hermes

CLI logo

CLI

Use Apify MCP with CLI

LangChain logo

LangChain

Use Apify MCP with LangChain

Vercel AI SDK logo

Vercel AI SDK

Use Apify MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use Apify MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use Apify MCP with LlamaIndex

CrewAI logo

CrewAI

Use Apify MCP with CrewAI

FAQ

Frequently asked questions

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

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 Apify tools.

Yes, absolutely. You can configure which Apify 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.

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 Apify data and credentials are handled as safely as possible.

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Karan skipped his own birthday party to fix our critical issue. It was 10pm and he diverted his Waymo to help us instead. This really sets the bar — it shows the commitment you need when users rely on your software.

Harsha Gaddipati
Harsha Gaddipati
Co-founder, Slashy

A lot of students tell us that the moment their connected tools start talking to each other inside Opennote feels almost magical. The agent just knows them, and it's immensely helped keep new users on the platform.

Abhi Arya
Abhi Arya
Co-founder, Opennote

We chose Composio over Pipedream because it delivered depth where it mattered — niche tools and tricky edge cases other platforms simply ignored. That gave us confidence to scale without compromising.

Nirman Dave
Nirman Dave
CEO, Zams

As a solo builder, shipping fast is life or death. The only way I can outcompete incumbents is by outmanoeuvring them. Getting bogged down managing agent auth would have been a death sentence.

Ryan Yu
Ryan Yu
Founder, Extra Thursday

Before Composio, adding tool integrations was slow and resource-intensive. Each one could take weeks of engineering time, and maintaining them meant constantly keeping up with API changes.

Tomisin Jenrola
Tomisin Jenrola
Founder & CEO, SwarmZero

With hands-on help from their founder, we integrated Gmail and Google Drive in just 30 minutes. This level of personal support and commitment is exactly what startups should strive for.

Jerome Leclanche
Jerome Leclanche
Co-Founder, Ingram Technologies